1  100
Next
 Stanford, California : HeurisTech Press, c1982.
 Description
 Book — 1 online resource (443 pages)
 Stanford, California : HeurisTech Press, c1982.
 Description
 Book — 1 online resource (659 pages)
4. Evolution, learning, and cognition [1988]
 Singapore ; Teaneck, N.J., USA : World Scientific, ©1988.
 Description
 Book — 1 online resource (x, 411 pages) : illustrations
 Summary

 PREFACE; CONTENTS; Part One MATHEMATICAL THEORY; Connectionist Learning Through Gradient Following; INTRODUCTION; CONNECTIONIST SYSTEMS; LEARNING; Supervised Learning vs. Associative Reinforcement Learning; FORMAL ASSUMPTIONS AND NOTATION; BACKPROPAGATION ALGORITHM FOR SUPERVISED LEARNING; Extended BackPropagation; REINFORCE ALGORITHMS FOR ASSOCIATIVE REINFORCEMENT LEARNING; Extended REINFORCE Algorithms; DISCUSSION; SUMMARY; REFERENCES; Efficient Stochastic Gradient Learning Algorithm for Neural Network; 1 Introduction; 2 Learning as Stochastic Gradient Descents.
 3 Convergence Theorems for First Order Schemes4 Convergence of the Second Order Schemes; 5 Discussion; References; INFORMATION STORAGE IN FULLY CONNECTED NETWORKS; 1 INTRODUCTION; 1.1 Neural Networks; 1.2 Organisation; 1.3 Notation; 2 THE MODEL OF McCULLOCHPITTS; 2.1 StateTheoretic Description; 2.2 Associative Memory; 3 THE OUTERPRODUCT ALGORITHM; 3.1 The Model; 3.2 Storage Capacity; 4 SPECTRAL ALGORITHMS; 4.1 OuterProducts Revisited; 4.2 Constructive Spectral Approaches; 4.3 Basins of Attraction; 4.4 Choice of Eigenvalues; 5 COMPUTER SIMULATIONS; 6 DISCUSSION; A PROPOSITIONS.
 B OUTERPRODUCT THEOREMSC PROOFS OF SPECTRAL THEOREMS; References; NEURONIC EQUATIONS AND THEIR SOLUTIONS;
 1. Introduction; 1
 .1. Reminiscing; 1
 .2. The 1961 Model; 1
 .3. Notation;
 2. Linear Separable NE; 2
 .1. Neuronic Equations; 2
 .2. Polygonal Inequalities; 2
 .3. Computation of the nexpansion of arbitrary l.s. functions; 2
 .4. Continuous versus discontinuous behaviour: transitions;
 3. General Boolean NE; 3
 .1. Linearization in tensor space; 3
 .2. Nextstate matrix; 3
 .3. Normal modes, attractors; 3
 .4. Synthesis of nets: the inverse problem; 3
 .5. Separable versus Boolean nets.
 Connections with spin formalismReferences; The Dynamics of Searches Directed by Genetic Algorithms; The Hyperplane Transformation.; The Genetic Algorithm as a HyperplaneDirected Search Procedure; (1) Description of the genetic algorithm; (2) Effects of the S's on the search generated by a genetic algorithm.; (3) An Example.; References.; PROBABILISTIC NEURAL NETWORKS;
 1. INTRODUCTION;
 2. MODELING THE NOISY NEURON; 2
 .1. Empirical Properties of Neuron and Synapse;
 22. Model of Shaw and Vasudevan; 2
 .3. Model of Little; 2
 .4. Model of Taylor.
 3. NONEQUILIBRIUM STATISTICAL MECHANICS OF LINEAR MODELS3.1. Statistical Law of Motion
 Markov Chain and Master Equation; 3.2. Entropy Production in the Neural; 3.3. Macroscopic Forces and Fluxes; 3.4. Conditions for Thermodynamic Equilibrium; 3.5. Implications for Memory Storage: How Dire?; 4. DYNAMICAL PROPERTIES OF NONLINEAR MODELS; 4.1. Views of Statistical Dynamics; 4.2. Multineuron Interactions, Revisited; 4.3. Cognitive Aspects of the Taylor Model; 4.4. Noisy RAMS and Noisy Nets; 5. THE END OF THE BEGINNING; ACKNOWLEDGMENTS; APPENDIX. TRANSITION PROBABILITIES IN 2NEURON NETWORKS.
(source: Nielsen Book Data)
5. How to build a person : a prolegomenon [1989]
 Pollock, John L.
 Cambridge, Mass. : MIT Press, ©1989.
 Description
 Book — 1 online resource (xi, 189 pages) : illustrations
 Summary

Building a person has been an elusive goal in artificial intelligence. This failure, John Pollock argues, is because the problems involved are essentially philosophical; what is needed for the construction of a person is a physical system that mimics human rationality. Pollock describes an exciting theory of rationality and its partial implementation in OSCAR, a computer system whose descendants will literally be persons.In developing the philosophical superstructure for this bold undertaking, Pollock defends the conception of man as an intelligent machine and argues that mental states are physical states and persons are physical objects as described in the fable of Oscar, the self conscious machine.Pollock brings a unique blend of philosophy and artificial intelligence to bear on the vexing problem of how to construct a physical system that thinks, is self conscious, has desires, fears, intentions, and a full range of mental states. He brings together an impressive array of technical work in philosophy to drive theory construction in AI. The result is described in his final chapter on "cognitive carpentry." John Pollock is Professor of Philosophy and Cognitive Science at the University of Arizona. A Bradford Book.
(source: Nielsen Book Data)
 Singapore ; Teaneck, N.J. : World Scientific, ©1990.
 Description
 Book — 1 online resource (vi, 222 pages) : illustrations
 Summary

 An intelligent imagebased computeraided education system: the prototype BIRDS / A.A. David, O. Thiery & M. Crehange
 PLAYMAKER: a knowledgebased approach to characterizing hydrocarbon plays / G. Biswas [and others]
 An expert system for interpreting mesoscale features in oceanographic satellite images / N. Krishnakumar [and others]
 An expert system for tuning particle beam accelerators / D.L. Lager, H.R. Brand & W.J. Maurer
 Expert system approach to assessments of bleeding predispositions in tonsillectomy/adenoidectomy patients / N.J. Pizzi & J.M. Gerrard
 Expert system approach using graph representation and analysis for variablestroke internalcombustion engine design / S.N.T. Shen, M.S. Chew & G.F. Issa
 A comparison of two new techniques for conceptual clustering / S.L. Crawford & S.K. Souders
 Querying an objectoriented database using free language / P. Trigano [and others]
 Adaptive planning for air combat maneuvering / I.C. Hayslip, J.P. Rosenking & J. Filbert
 AM/AG model: a hierarchical social system metaphor for distributed problem solving / D.G. Shin & J. Leone
 CAUSA
 A tool for modelbased knowledge acquisition / W. Dilger & J. Moller
 PRIOPS: a realtime production system architecture for programming and learning in embedded systems / D.E. Parson & G.D. Blank.
(source: Nielsen Book Data)
7. Naturally intelligent systems [1990]
 Caudill, Maureen.
 Cambridge, Mass. : MIT Press, ©1990.
 Description
 Book — 1 online resource (304 pages) : illustrations
 Summary

For centuries, people have been fascinated by the possibility of building an artificial system that behaves intelligently. Now there is a new entry in this arena  neural networks. Naturally Intelligent Systems offers a comprehensive introduction to these exciting systems. It provides a technically accurate, yet downtoearth discussion of neural networks, clearly explaining the underlying concepts of key neural network designs, how they are trained, and why they work. Throughout, the authors present actual applications that illustrate neural networks' utility in the new world.
(source: Nielsen Book Data)
Naturally Intelligent Systems offers a comprehensive introduction to neural networks.
(source: Nielsen Book Data)
For centuries, people have been fascinated by the possibility of building an artificial system that behaves intelligently. From Mary Shelley's Frankenstein monster to the computer intelligence of HAL in 2001, scientists have been cast in the role of creator of such devices. Now there is a new entry into this arena, neural networks, and "Naturally Intelligent Systems explores these systems to see how they work and what they can do. Neural networks are not computers in any traditional sense, and they have little in common with earlier approaches to the problem of fabricating intelligent behavior. Instead, they are information processing systems that are physically modeled after the structure of the brain and that are "trained to perform a task rather than programmed like a computer. Neural networks, in fact, provide a tool with problemsolving capabilities  and limitations  strikingly similar to those of animals and people. In particular, they are successful in applications such as speech, vision, robotics, and pattern recognition. "Naturally Intelligent Systems offers a comprehensive introduction to these exciting systems. It provides a technically accurate, yet downtoearth discussion of neural networks. No particular mathematical background is necessary; it is written for all interested readers. "Naturally Intelligent Systents clearly explains the underlying concepts of key neural network designs, how they are trained, and why they work. It compares their behavior to the natural intelligence found in animals  and people. Throughout, Caudill and Butler bring the field into focus by presenting actual applications that illustrate neural networks' utility in the real world. MaureenCaudill is President of Adaptics, a neural network consulting company in San Diego and author of the popular "Neural Network Primer" articles that appear regularly in "AI Expert. Charles Butler is a Senior Principal Scientist at Physical Sciences in Alexandria, Virginia. He is a specialist in neural network application development. A Bradford Book.
(source: Nielsen Book Data)
 Judd, J. Stephen.
 Cambridge, Mass. : MIT Press, ©1990.
 Description
 Book — 1 online resource (150 pages) : illustrations
 Summary

 1. Neural networks: hopes, problems, and goals
 2. The loading problem
 3. Other studies of learning
 4. The intractability of loading
 5. Subcases
 6. Shallow architectures
 7. Memorization and generalization
 8. Conclusion.
(source: Nielsen Book Data)
 Neurale netværk. English
 Brunak, Søren.
 Singapore ; Teaneck, N.J., USA : World Scientific, ©1990.
 Description
 Book — 1 online resource (180 pages) : illustrations
 Summary

Both specialists and laymen will enjoy reading this book. Using a lively, nontechnical style and images from everyday life, the authors present the basic principles behind computing and computers. The focus is on those aspects of computation that concern networks of numerous small computational units, whether biological neural networks or artificial electronic devices.
(source: Nielsen Book Data)
10. Applications of learning & planning methods [1991]
 Singapore ; Teaneck, N.J. : World Scientific, 1991.
 Description
 Book — 1 online resource
 Summary

 Ch 1. Embedding learning in a general framebased architecture / T. Tanaka and T.M. Mitchell
 ch. 2. Connectionist learning with Chebychev networks and analyses of its internal representation / A. Narnatame
 ch. 3. Layered inductive learning algorithms and their computational aspects / H. Madala
 ch. 4. An approach to combining explanationbased and neural learning algorithms / J.W. Shavlik and G.G. Towell
 ch. 5. The application of symbolic inductive learning to the acquisition and recognition of noisy texture concepts / P.W. Pachowicz
 ch. 6. Automating technology adaptation in design synthesis / J.R. Kipps and D.D. Gajski
 ch. 7. Connectionist production systems in local and hierarchical representation / A. Sohn and J.L. Gaudiot
 ch. 8. A parallel architecture for AI nonlinear planning / S. Lee and K. Chung
 ch. 9. Heuristic tree search using nonparametric statistical inference methods / W. Zhang and N.S.V. Rao
 ch. 10. An A* approach to robust plan recognition for intelligent interfaces / R.J. CalistriYeh
 ch. 11. Differential A*: an adaptive search method illustrated with robot path planning for moving obstacles & goals, and an uncertain environment / K.I. Trovato
 ch. 12. Path planning under uncertainty / F. Yegenoglu and H.E. Stephanou
 ch. 13. Knowledgebased acquisition in realtime path planning in unknown space / N.G. Bourbakis
 ch. 14. Path planning for two cooperating robot manipulators / Q. Xue and P.C.Y. Sheu.
(source: Nielsen Book Data)
 Russell, Stuart J. (Stuart Jonathan), 1962
 Cambridge, Mass. : MIT Press, ©1991.
 Description
 Book — 1 online resource (xx, 200 pages) : illustrations
 Summary

 Limited rationality
 execution architectures for decision procedures
 metareasoning architecture
 rational metareasoning
 application to game playing
 application to problem solving search
 learning the value of computation
 toward limited rational agents.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
Like Mooki, the hero of Spike Lee's film "Do the Right Thing" artificially, intelligent systems have a hard time knowing what to do in all circumstances. Classical theories of perfect rationality prescribe the "right thing" for any occasion, but no finite agent can compute their prescriptions fast enough. In "Do the Right Thing", the authors argue that a new theoretical foundation for artificial intelligence can be constructed in which rationality is a property of "programs" within a finite architecture, and their behaviour over time in the task environment, rather than a property of individual decisions. "Do The Right Thing" suggests that the rich structure that seems to be exhibited by humans, and ought to be exhibited by AI systems, is a necessary result of the pressure for optimal behaviour operating within a system of strictly limited resources. It provides an outline for the design of new intelligent systems and describes theoretical and practical tools for bringing about intelligent behaviour in finite machines. The tools are applied to game planning and realtime problem solving, with surprising results.
(source: Nielsen Book Data)
 Aleksandrov, V. V. (Viktor Vasilʹevich)
 Singapore ; Teaneck, N.J. : World Scientific, ©1991.
 Description
 Book — 1 online resource (viii, 203 pages) : illustrations (some color)
 Summary

 AUTHORS' NOTES AND ACKNOWLEDGEMENTS; INTRODUCTION; 1.1. Objectives of this Book; 1.2. The Seeing Eye and the Knowing Eye
 1 IMAGE AND COMPUTER; 1.1. A Short History; 1.2. The Computer's Eye; 1.3. A Beetle and an AntHill; 1.4. Features and Models; 2 HOW HUMANS SEE THE WORLD; 2.1. The Eye and the Brain; 2.2. The Level of Preattention; 2.3. Right and Left Vision; 2.4. Images and Words; 3 CONVERSATIONS WITH A COMPUTER; 3.1. From a Point to a Region; 3.2. From a Region to an Object; 3.3. From an Object to a Situation; 4 AN APOLOGIA FOR VISION; 4.1. The Evolution of Vision.
 4
 .2. Vision and Thinking4
 .3. Recollection of the Future; 4
 .4. Cognition through Vision; 5 CREATING A NEW WORLD; 5
 .1. From Elements to the System; 5
 .2. Back to Nature; 5
 .3. Who Do We Think They Are?; CONCLUSIONS; PLATES; REFERENCES; ILLUSTRATIONS; INDEX.
(source: Nielsen Book Data)
 Singapore ; River Edge, N.J. : World Scientific, ©1991.
 Description
 Book — 1 online resource (iii, 159 pages) : illustrations
 Summary

 Introduction, C.H. Chen
 combined neuralnet/knowledgebased adaptive systems for large scale dynamic control, A.D.C. Holden and S.C. Suddarth
 a connectionist incremental expert system combining production systems and associative memory, H.F. Yin and P. Liang
 optimal hidden units for twolayer nonlinear feedforward networks, T.D. Sanger
 an incremental fine adjustment algorithm for the design of optimal interpolating networks, S.K. Sin and R.J.P. deFigueiredo
 on the asymptotic properties of recurrent neural networks for optimization, J. Wang
 a realtime image segmentation system using a connectionist classifier architecture, W.E. Blanz and S.L. Gish
 segmentation of ultrasonic images with neural network technology's on automatic active sonar classifier development, T.B. Haley
 on the relationships between statistical pattern recognition and artificial neural networks, C.H. Chen.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Singapore ; River Edge, N.J. : World Scientific, ©1992.
 Description
 Book — 1 online resource (xxiv, 705 pages) : illustrations
 Summary

 An introduction to artificial intelligence, N.G. Bourbakis
 fundamental methods for horn logic and AI applications, E. Kounalis and P. Marquis
 applications of genetic algorithms to permutation problems, F. Petry and B. Buckles
 extracting procedural knowledge from software systems using inductive learning in the PM system, R. Reynolds and E. Zannoni
 resource oriented parallel planning, S. Lee and K. Chung
 advanced parsing technology for knowledge based shells, J. Kipps
 analysis and synthesis of intelligent systems, W. Arden
 document analysis and recognition, S.N. Srihari et al
 signal understanding  an AI approach to modulation and classification, J.E. Whelchel et al
 and others.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Dreyfus, Hubert L.
 Cambridge, Mass. : MIT Press, ©1992.
 Description
 Book — 1 online resource (liii, 354 pages)
 Summary

 Ten years of research in artificial intelligence (19571967)
 Cognitive simulation (19571962)
 Semantic information processing (19621967)
 Assumptions underlying persistent optimism
 Biological assumption
 Psychological assumption
 Epistemological assumption
 Ontological assumption
 Alternatives to the traditional assumptions
 The role of the body in intelligent behavior
 The situation: orderly behavior without recourse to rules
 The situation as a function of human needs
 Conclusion: the scope and limits of artificial reason
 The limits of artificial intelligence
 The future of artificial intelligence.
(source: Nielsen Book Data)
 Clark, Andy, 1957
 Cambridge, Mass. : MIT Press, ©1993.
 Description
 Book — 1 online resource (xiii, 252 pages) : illustrations
 Summary

 Part 1 Melting the inner code: computational models, syntax, and the folk solids
 connectionism, code, and context
 what networks know
 what networks don't know
 concept, category and prototype. Part 2 From code to process: the presence of a symbol
 the role of representational trajectories
 the cascade of significant virtual machines
 associative learning in a hostile world
 the fate of the folk
 associative engines  the next generation.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
17. Neural network learning and expert systems [1993]
 Gallant, Stephen I.
 Cambridge, Mass. : MIT Press, ©1993.
 Description
 Book — 1 online resource (xvi, 365 pages) : illustrations
 Summary

 1. Introduction and important definitions
 2. Representation issues
 3. Perceptron learning and the pocket algorithm
 4. Winnertakeall groups or linear machines
 5. Autoassociators and oneshot learning
 6. Mean squared error (MSE) algorithms
 7. Unsupervised learning
 8. The distributed method and radial basis functions
 9. Computational learning theory and the BRD algorithm
 10. Constructive algorithms
 11. Backpropagation
 12. Backpropagation : variations and applications
 13. Simulated annealing and boltzmann machines
 14. Expert systems and neural networks
 15. Details of the MACIE system
 16. Noise, redundancy, fault detection, and bayesian decision theory
 17. Extracting rules from networks.
(source: Nielsen Book Data)
18. Advances in genetic programming. [Voume 1] [1994]
 Cambridge, Massachusetts : The MIT Press, [1994]
 Description
 Book — 1 online resource (ix, 476 pages) : illustrations
 Summary

 A perspective on the work in this book / Kenneth E. Kinnear, Jr.
 Introduction to genetic programming / John R. Koza
 The evolution of evolvability in genetic programming / Lee Altenberg
 Genetic programming and emergent intelligence / Peter J. Angeline
 Scalable learning in genetic programming using automatic function definition / John R. Koza
 Alternatives in automatic function definition : a comparison of performance / Kenneth E. Kinnear, Jr.
 The donut problem : scalability, generalization and breeding policies in genetic programming / Walter Alden Tackett, Aviram Carmi
 Effects of locality in individual and population evolution / Patrik D'haeseleer, Jason Bluming
 The evolution of mental models / Astro Teller
 Evolution of obstacle avoidance behavior : using noise to promote robust solutions / Craig W. Reynolds
 Pygmies and civil servants / Conor Ryan
 Genetic programming using a minimum decsription length principle / Hitoshi Iba, Hugo de Garis, Taisuke Sato
 Genetic programming in C++: implementation issues / Mike J. Keith, Martin C. Martin. A compiling genetic programming system that directly manipulates the machine code / Peter Nordin
 Automatic generation of programs for crawling and walking / Graham Spencer
 Genetic programming for the acquisition of double auction market strategies / Martin Andrews, Richard Prager
 Two scientific applications of genetic programming : stack filters and nonlinear equation fitting to chaotic data / Howard Oakley
 The automatic generation of plans for a mobile robot via genetic programming with automatically defined functions / Simon G. Handley
 Competitively evolving decision trees against fixed training cases for natural language processing / Eric V. Siegel
 Cracking and coevolving randomizers / Jan Jannink
 Optimizing confidence of text classification by evolution of symbolic expressions / Brij Masand
 Evolvable 3D modeling for modelbased object recognition systems / Thang Nguyen, Thomas Huang
 Automatically defined features : the simultaneous evolution of 2dimensional feature detectors and an algorithm for using them / David Andre
 Genetic micro programming of neural networks / Frédéric Gruau.
(source: Nielsen Book Data)
There is increasing interest in genetic programming by both researchers and professional software developers. These twentytwo invited contributions show how a wide variety of problems across disciplines can be solved using this new paradigm. Advances in Genetic Programming reports significant results in improving the power of genetic programming, presenting techniques that can be employed immediately in the solution of complex problems in many areas, including machine learning and the simulation of autonomous behavior. Popular languages such as C and C++ are used in many of the applications and experiments, illustrating how genetic programming is not restricted to symbolic computing languages such as LISP. Researchers interested in getting started in genetic programming will find information on how to begin, on what public domain code is available, and on how to become part of the active genetic programming community via electronic mail. A major focus of the book is on improving the power of genetic programming. Experimental results are presented in a variety of areas, including adding memory to genetic programming, using locality and "demes" to maintain evolutionary diversity, avoiding the traps of local optima by using coevolution, using noise to increase generality, and limiting the size of evolved solutions to improve generality. Significant theoretical results in the understanding of the processes underlying genetic programming are presented, as are several results in the area of automatic function definition. Performance increases are demonstrated by directly evolving machine code, and implementation and design issues for genetic programming in C++ are discussed.
(source: Nielsen Book Data)
19. Circuit complexity and neural networks [1994]
 Parberry, Ian.
 Cambridge, Mass. : MIT Press, ©1994.
 Description
 Book — 1 online resource (xxix, 270 pages) : illustrations
 Summary

 Computers and computation
 the discrete neuron
 the Boolean neuron
 alternating circuits
 small, shallow alternating circuits
 threshold circuits
 cyclic networks
 probabilistic neural networks.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
Neural networks usually work adequately on small problems but can run into trouble when they are scaled up to problems involving large amounts of input data. Circuit Complexity and Neural Networks addresses the important question of how well neural networks scale  that is, how fast the computation time and number of neurons grow as the problem size increases. It surveys recent research in circuit complexity (a robust branch of theoretical computer science) and applies this work to a theoretical understanding of the problem of scalability.
(source: Nielsen Book Data)
 Kearns, Michael J.
 Cambridge, Mass. : MIT Press, ©1994.
 Description
 Book — 1 online resource (xii, 207 pages) : illustrations
 Summary

 The probably approximately correct learning model
 Occam's razor
 the VapnikChervonenkis dimension
 weak and strong learning
 learning in the presence of noise
 inherent unpredictability
 reducibility in PAC learning
 learning finite automata by experimentation
 appendix  some tools for probabilistic analysis.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Crockett, Larry.
 Norwood, N.J. : Ablex Pub. Corp., ©1994.
 Description
 Book — 1 online resource (viii, 216 pages) : illustrations
 Summary

 Introduction: the Turing test in light of the frame problem
 Algorithmic machines and computer learning
 Computer simulation and user illusions
 The Dreyfus critique and the frame problem
 The Turing test, Dennett's defense of the test, and mindlike programs
 The relation of the frame problem to the Turing test
 Two major critiques of the test: Searle and Gunderson
 The frame problem, philosophy, and AI's understanding of intelligence.
(source: Nielsen Book Data)
22. Artificial minds [1995]
 Franklin, Stan.
 Cambridge, Mass. : MIT Press, ©1995.
 Description
 Book — 1 online resource (xi, 449 pages) : illustrations
 Summary

 Mechanisms of mind
 the nature of mind and the mindbody problem
 animal minds
 symbolic AI
 the first AI debate
 connectionism
 the second AI debate
 evolution, natural and artificial
 artificial life
 multiplicity of mind
 what do I do now?
 what's out there?
 remembering and creating
 representation and the third AI debate
 into the future
 an emerging new paradigm of mind?.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
Recent decades have produced a blossoming of research in artificial systems that exhibit important properties of mind. But what exactly is this dramatic new work and how does it change the way we think about the mind, or even about who or what has mind?
(source: Nielsen Book Data)
23. Fuzzy logic and soft computing [1995]
 Singapore ; River Edge, NJ : World Scientific, ©1995.
 Description
 Book — 1 online resource (x, 497 pages) : illustrations
 Summary

 Fuzzy logic and genetic algorithms
 learning
 fuzzy and hybrid systems
 decision and aggregation techniques
 fuzzy logic in databases
 foundations of fuzzy logic
 applications of fuzzy sets.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
24. Goaldriven learning [1995]
 Cambridge, Mass. : MIT Press, ©1995.
 Description
 Book — 1 online resource (xxii, 507 pages) : illustrations
 Summary

 1. Learning, goals, and learning goals / by Ashwin Ram and David B. Leake
 2. Planning to learn / by Lawrence Hunter
 3. Quantitative results concerning the utility of explanationbased learning / by Steven Minton
 4. The use of explicit goals for knowledge to guide inference and learning / by Ashwin Ram and Lawrence Hunter
 5. Deriving categories to achieve goals / by Lawrence W. Barsalou
 6. Harpoons and long sticks : the interaction of theory and similarity in rule induction / by Edward J. Wisniewski and Douglas L. Medin
 7. Introspective reasoning using metaexplanations for multistrategy learning / by Ashwin Ram and Michael T. Cox
 8. Goaldirected learning : a decisiontheoretic model for deciding what to learn next / by Marie desJardins
 9. Goalbased explanation evaluation / by David B. Leake
 10. Planning to perceive / by Louise Pryor and Gregg Collins
 11. Planning and learning in PRODIGY : overview of an integrated architecture / by Jaime Carboneil [and others]
 12. A learning model for the selection of problemsolving strategies in continuous physical systems / by Xiaodong Xia and DifYan Yeung
 13. Explicitly biased generalization / by Diana Gordon and Donald Perlis
 14. Three levels of goal orientation in learning / by Evelyn Ng and Carl Bereiter
 15. Characterizing the application of computer simulations in education : instructional criteria / by Jos J.A. van Berkum [and others]
 16. Goaldriven learning : fundamental issues and symposium report / by David B. Leake and Ashwin Ram
 17. Storage side effects : studying processing to understand learning / by Lawrence W. Barsalou
 18. Goaldriven learning in multistrategy reasoning and learning systems / by Ashwin Ram, Michael T. Cox and S. Narayanan
 19. Inference to the best plan : a coherence theory of decision / by Paul Thagard and Elija Millgram
 20. Toward goaldriven integration of explanation and action / by David B. Leake
 21. Learning as goaldriven inference / by Ryszard Michalski and Ashwin Ram.
(source: Nielsen Book Data)
In cognitive science, artificial intelligence, psychology, and education, a growing body of research supports the view that the learning process is strongly influenced by the learner's goals. The fundamental tenet of goaldriven learning is that learning is largely an active and strategic process in which the learner, human or machine, attempts to identify and satisfy its information needs in the context of its tasks and goals, its prior knowledge, its capabilities, and environmental opportunities for learning. This book brings together a diversity of research on goaldriven learning to establish a broad, interdisciplinary framework that describes the goaldriven learning process. It collects and solidifies existing results on this important issue in machine and human learning and presents a theoretical framework for future investigations.
(source: Nielsen Book Data)
 AlAsady, Raad.
 Norwood, N.J. : Ablex Pub., ©1995.
 Description
 Book — 1 online resource (x, 204 pages) : illustrations
 Summary

Within artificial intelligence, the need to create sophisticated, intelligent behaviour based on commonsense reasoning has long been recognized. Research has demonstrated that formalism for dealing with common sense reasoning require nonmonotonic capabilities where, typically, inferences based on incomplete knowledge need to be revised in light of later information which fills in some of the gaps.
(source: Nielsen Book Data)
 Teh, H. H.
 Singapore ; River Edge, NJ : World Scientific, ©1995.
 Description
 Book — 1 online resource (xv, 504 pages) : illustrations
 Summary

 The Road to Intelligent Machines
 The Power and Limitations of Perceptrons
 Neural Logic Networks
 Probabilistic Neural Logic Networks
 Fuzzy Neural Logic Networks
 Temporal Neural Logic Networks
 Neural Logic Programming
 Connectionist Expert Systems
 Fuzzy Knowledge Processing
 The Art of Guessing.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 French, Robert M. (Robert Matthew), 1951
 Cambridge, Mass. : MIT Press, 1995.
 Description
 Book — 1 online resource (xvi, 190 pages) : illustrations
 Summary

 From recognition to analogymaking  the central role of slippage
 the Tabletop microdomain
 the architecture of Tabletop
 Tabletop's performance up close
 Tabletop's personality profile
 comparisons with other work
 summary and conclusions.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
The research described in this book is based on the premise that human analogymaking is an extension of our constant background process of perceivingin other words, that analogymaking and the perception of sameness are two sides of the same coin. Foreword by Daniel Dennett While it is fashionable today to dismiss the "bad old days" of artificial intelligence and rave about emergent selforganizing systems, Robert French has created a model of human analogymaking that attempts to bridge the gap between classical topdown AI and more recent bottomup approaches. The research described in this book is based on the premise that human analogymaking is an extension of our constant background process of perceivingin other words, that analogymaking and the perception of sameness are two sides of the same coin. At the heart of the author's theory and computer model of analogymaking is the idea that the buildingup and the manipulation of representations are inseparable aspects of mental functioning, in contrast to traditional AI models of highlevel cognitive processes, which have almost always depended on a clean separation. A computer program called Tabletop forms analogies in a microdomain consisting of everyday objects on a table set for a meal. The theory and the program rely on the idea that myriad stochastic choices made on the microlevel can add up to statistical robustness on a macrolevel. To illustrate this, French includes the results of thousands of runs of his program on several dozen interrelated analogy problems in the Tabletop microworld. French's work is exciting not only because it reveals analogymaking to be an extension of our complex and subtle ability to perceive sameness but also because it offers a computational model of mechanisms underlying these processes. This model makes significant strides in putting into practice microlevel stochastic processing, distributed processing, simulated parallelism, and the integration of representationbuilding and representationprocessing. A Bradford Book.
(source: Nielsen Book Data)
28. Analogue imprecision in MLP training [1996]
 Edwards, Peter J. (Peter John)
 Singapore ; River Edge, NJ : World Scientific, ©1996.
 Description
 Book — 1 online resource (xi, 178 pages) : illustrations
 Summary

 Neural network performance metrics
 noise in neural implementations
 simulation requirements and environment
 fault tolerance
 generalisation ability
 learning trajectory and speed.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Briscoe, Garry.
 Norwood, N.J. : Ablex Pub. Corp., ©1996.
 Description
 Book — 1 online resource (353 pages) : illustrations
 Summary

Machine learning is a relatively new branch of artificial intelligence. The field has undergone a significant period of growth in the 1990s, with many new areas of research and development being explored.
(source: Nielsen Book Data)
 Bäck, Thomas, 1963
 New York : Oxford University Press, 1996.
 Description
 Book — 1 online resource (xii, 314 pages) : illustrations
 Summary

 PART I: A COMPARISON OF EVOLUTIONARY ALGORITHMS
 PART II: EXTENDING GENETIC ALGORITHMS.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
This book compares the three most prominent representatives of evolutionary algorithms  genetic algorithms, evolution strategies, and evolutionary programming  computational methods at the border between computer science and evolutionary biology. The algorithms are explained within a common formal framework, thereby clarifying the similarities and differences of these methods. The author also presents new results regarding the role of mutation and selection in genetic algorithms and uses a metaevolutionary approach to confirm some of the theoretical results.
(source: Nielsen Book Data)
 Kasabov, Nikola K.
 Cambridge, Mass. : MIT Press, ©1996.
 Description
 Book — 1 online resource (xvi, 550 pages) : illustrations Digital: text file; PDF.
 Summary

 1. The faculty of knowledge engineering and problem solving
 2. Knowledge engineering and symbolic artificial intelligence
 3. From fuzzy sets to fuzzy systems
 4. Neural networks : theoretical and computational models
 5. Neural networks for knowledge engineering and problem solving
 6. Hybrid symbolic, fuzzy, and connectionist systems : toward comprehensive artificial intelligence
 7. Neural networks, fuzzy systems, and nonlinear dynamical systems. chaos ; toward new connectionist and fuzzy logic models.
(source: Nielsen Book Data)
Neural networks and fuzzy systems are different aprpoaches to introducing humanlike reasoning into expert systems. This text combines the study of these two subjects, their basics and their use, along with symbolic AI methods to build comprehensive artificial intelligence systems. Kasabov describes rulebased and connectionist techniques and then their combinations, with fuzzy logic included, showing the application of the different techniques to a set of simple prototype problems, which makes comparisons possible. A particular feature of the text is that it is filled with applications in engineering, business and finance. AI problems that cover most of the applicationoriented research in the field (pattern recognition, speech and image processing, classification, planning, optimization, prediction, control, decision making, and game simulations) are discussed and illustrated with concrete examples. Intended both as a text for advanced undergraduate and postgraduate students as well as a reference for researchers in the field of knowledge engineering, "Foundations of Neural Networks, Fuzzy Systems and Knowledge Engineering" has chapters structured for various levels of teaching and includes work by the author along with the classic material. Data sets for the examples in the book as well as an integrated software environment that can be used to solve the problems and do the exercises at the end of each chapter are available free through anonymous ftp.
(source: Nielsen Book Data)
 Saratchandran, P.
 Singapore ; River Edge, NJ : World Scientific, ©1996.
 Description
 Book — 1 online resource (xviii, 202 pages)
 Summary

 Hardware and software aspects
 transputer topologies for parallel implementation
 comparison between serial and parallel implementation
 analysis and implementation for equal distribution of the training set in a homogeneous transputer array
 analysis and implementation for unequal distribution of the training set in a homogeneous transputer array
 analysis and implementation for unequal distribution of the training set in a heterogeneous transputer array
 conclusion.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Zhang, YanQing.
 Singapore ; River Edge, N.J. : World Scientific, 1997.
 Description
 Book — 1 online resource (xii, 186 pages) : illustrations
 Summary

 Fuzzy compensation principles
 normal fuzzy reasoning methodology
 compensatory genetic fuzzy neural networks
 fuzzy knowledge rediscovery in fuzzy rule bases
 fuzzy catpole balancing control systems
 fuzzy knowledge compression and expansion
 highly nonlinear system modelling and prediction
 fuzzy moves in fuzzy games
 genetic neurofuzzy pattern recognition
 constructive approach to modelling fuzzy systems.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Singapore ; River Edge, NJ : World Scientific Pub., ©1997.
 Description
 Book — 1 online resource (x, 240 pages) : illustrations
 Summary

 Helicopter flight control with fuzzy logic and genetic algorithms, C. Philips et al
 skill acquisition and skillbased motion planning for hierarchical intelligent control of a redundant manipulator, T. Shibata
 a creative design of fuzzy logic controller using a genetic algorithm, T. Hashiyama et al
 automatic fuzzy tuning and its applications, H. Ishigami et al
 an evolutionary algorithm for fuzzy controller synthesis and optimization based on SGSThomson's W.A.R.P. fuzzy processor, R. Poluzzi et al
 online selfstructuring fuzzy inference systems for function approximation, H. Bersini
 fuzzy classification based on adaptive networks and genetic algorithms, C.T. Sun and J.S. Jang
 intelligent systems for fraud detection, J. Kingdon
 genetic algorithms for query optimization in information retrieval  relevance feedback, D.H. Kraft et al
 fuzzy fitness assignment in an interactive genetic algorithm for a cartoon face search, K. Nishio et al
 an evolutionary approach to simulate cognitive feedback learning in medical domain, H.S. Lopes et al
 a classified review on the combination fuzzy logicgenetic algorithms bibliography  19891995, O. Cordon et al.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
35. Machine vision [1997]
 Norwood, N.J. : Ablex Pub. Corp., ©1997.
 Description
 Book — 1 online resource (vii, 305 pages) : illustrations
36. Artificial intelligence and automation [1998]
 Singapore ; River Edge, NJ : World Scientific, ©1998.
 Description
 Book — 1 online resource (xix, 536 pages) : illustrations
 Summary

 A new way to acquire knowledge, H.Y. Wang
 an SPN knowledge representation scheme, J. Gattiker and N. Bourbakis
 on the deep structures of word problems and their construction, F. Gomez
 resolving conflicts in inheritance reasoning with statistical approach, C. Lee
 integrating high and low level computer vision for scene understanding, R. Malik and S. So
 the evolution of commercial AI tools  the first decade, F. HayesRoth
 reengineering  the AT generation  billions on the table, J.S. Minor, Jr.
 an intelligent tool for discovering data dependencies in relational DBS, P. Gavaskar and F. Golshani
 a casebased reasoning (CBR) tool to assist traffic flow, B. Das and S. Bayles
 a study of financial expert system based on flops, T. Kaneko and K. Takenaka
 an associative data parallel compilation model for tight integration of high performance knowledge retrieval and computation, A. Bansal
 software automation  from silly to intelligent, X. Jiafu et al
 software engineering using artificial intelligence  the knowledge based software assistant, D. White
 knowledge based derivation of programmes from specs, T. Weight et al
 automatic functional model generation for parallel fault design error simulations, S.E. Chang and S. Szygenda
 visual reverse engineering using SPN for automated diagnosis and functional simulation of digital circuits, J. Gattiker and S. Mertoguno
 the impact of AI in VLSI design automation, M. Mortazavi and N. Bourbakis
 the automated acquisition of subcategorization of verbs, nouns and adjectives from sample sentences, F. Gomez
 general method for planning and rendezvous problems, K. Trovato
 learning to improve path planning performance, P.C. Chen
 incremental adaptation as a method to improve reactive behaviour, A.J. Hendriks and D.M. Lyons
 an SPNneural planning methodology for coordination of multiple robotic arms with constrained placement, N. Bourbakis and A. Tascillo.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Thornton, Christopher James.
 2nd ed.  New York : AMACOM, ©1998.
 Description
 Book — 1 online resource (xvii, 363 pages) : illustrations
 Singapore ; River Edge, N.J. : World Scientific, ©1998.
 Description
 Book — 1 online resource (xiii, 485 pages) : illustrations
 Summary

 Approximate reasoning about comlpex objects in distributed systems  rough mereological formulation
 FOOD  fuzzy objectoriented design
 approximating block access in database systems
 the computer zoo in a box
 expert system design
 automating creation of computer programs for design circuits using genetic programming
 selforganizing maps
 knowledgebased techniques for software quality management
 object networks in developing intelligent systems
 application of genetic programming in software quality prediction
 neural networks for software quality prediction
 fuzzy Petri nets and Choquet integral in software cost estimation
 nonCartesian approach to software development
 inductive programming.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Frey, Brendan J.
 Cambridge, Mass : MIT Press, ©1998.
 Description
 Book — 1 online resource (xiii, 195 pages) : illustrations Digital: text file.PDF.
 Summary

 1. Introduction
 2. Probabilistic inference in graphical models
 3. Pattern classification
 4. Unsupervised learning
 5. Fata compression
 6. Vhannel coding
 7. Future research directions.
(source: Nielsen Book Data)
A variety of problems in machine learning and digital communication deal with complex but structured natural or artificial systems. In this book, Brendan J. Frey uses graphical models as an overarching framework to describe and solve problems of pattern classification, unsupervised learning, data compression, and channel coding. Using probabilistic structures such as Bayesian belief networks and Markov random fields, he is able to describe the relationships between random variables in these systems and to apply graphbased inference techniques to develop new algorithms.
(source: Nielsen Book Data)
 Frey, Brendan J.
 Cambridge, Mass : MIT Press, ©1998.
 Description
 Book — 1 online resource (xiii, 195 pages) : illustrations.
 Summary

 1. Introduction
 2. Probabilistic inference in graphical models
 3. Pattern classification
 4. Unsupervised learning
 5. Fata compression
 6. Vhannel coding
 7. Future research directions.
(source: Nielsen Book Data)
A variety of problems in machine learning and digital communication deal with complex but structured natural or artificial systems. In this book, Brendan J. Frey uses graphical models as an overarching framework to describe and solve problems of pattern classification, unsupervised learning, data compression, and channel coding. Using probabilistic structures such as Bayesian belief networks and Markov random fields, he is able to describe the relationships between random variables in these systems and to apply graphbased inference techniques to develop new algorithms.
(source: Nielsen Book Data)
 Frey, Brendan J.
 Cambridge, Mass : MIT Press, ©1998.
 Description
 Book — 1 online resource (xiii, 195 pages) : illustrations.
 Summary

 1. Introduction
 2. Probabilistic inference in graphical models
 3. Pattern classification
 4. Unsupervised learning
 5. Fata compression
 6. Vhannel coding
 7. Future research directions.
(source: Nielsen Book Data)
A variety of problems in machine learning and digital communication deal with complex but structured natural or artificial systems. In this book, Brendan J. Frey uses graphical models as an overarching framework to describe and solve problems of pattern classification, unsupervised learning, data compression, and channel coding. Using probabilistic structures such as Bayesian belief networks and Markov random fields, he is able to describe the relationships between random variables in these systems and to apply graphbased inference techniques to develop new algorithms.
(source: Nielsen Book Data)
42. Implementation techniques [1998]
 San Diego, Calif. : Academic Press, ©1998.
 Description
 Book — 1 online resource (xviii, 401 pages) : illustrations
 Summary

 Bianchini, Frasconi, Gori, and Maggini, Optimal Learning in Artificial Neural Networks: A Theoretical View. Kanjilal, Orthogonal Transformation Techniques in the Optimization of Feedforward Neural Network Systems. Museli, Sequential Constructive Techniques. Yu, Xu, and Wang, Fast Backpropagation Training Using Optimal Learning Rate and Momentum. Angulo and Torras, Learning of Nonstationary Processes. Schaller, Constraint Satisfaction Problems. Yang and Chen, Dominant Neuron Techniques. Lin, Chiang, and Kim, CMACbased Techniques for Adaptive Learning Control. Deco, Information Dynamics and Neural Techniques for Data Analysis. Gorinevsky, Radial Basis Function Network Approximation and Learning in TaskDependent Feedforward Control of Nonlinear Dynamical Systems.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
43. Optimization techniques [1998]
 Leondes, Cornelius T.
 San Diego : Academic Press, 1998.
 Description
 Book — 1 online resource (xxii, 398 pages) : illustrations
 Summary

 Albertini and Pra, Recurrent Neural Networks: Identification and Other System Theoretic Properties. Anderson and Titterington, Boltzmann Machines: Statistical Associations and Algorithms for Training Anderson and Titterington. Campbell, Constructive Learning Techniques for Designing Neural Network Systems. Mehrotra and Mohan, Modular Neural Networks. Xu and Kwong, Associative Memories. Fry and Sova, A Logical Basis for Neural Network Design.Hoekstra, Duin, and Kraaijveld, Neural Networks Applied to Data Analysis. Zhang and Wang, MultiMode Single Neuron Arithmetics.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
44. Advances in genetic programming. Volume III [1999]
 Cambridge, Mass. : MIT Press, [1999]
 Description
 Book — 1 online resource (476 pages) : illustrations
 Summary

 Contributors
 Acknowledgments
 1. An Introduction to the Third Volume / Lee Spector, William B. Langdon, UnaMay O'Reilly, Peter J. Angelino
 I. Applications
 2. An Automatic Software ReEngineering Tool Based on Genetic Programming / Conor Ryan and Laur Ivan
 3. CAD Surface Reconstruction from Digitized 3D Point Data with a Genetic Programming/Evolution Strategy Hybrid / Robert E. Keller, Wolfgang Banzhaf, Jorn Mehnen and Klaus Weinert
 4. A Genetic Programming Approach for Robust Language Interpretation / Carolyn Penstein Rose
 5. Time Series Modeling Using Genetic Programming: An Application to RainfallRunoff Models / Peter A. Whigham and Peter F. Crapper
 6. Automatic Synthesis, Placement, and Routing of Electrical Circuits by Means of Genetic Programming / John R. Koza and Forest H. Bennett III
 7. Quantum Computing Applications of Genetic Programming / Lee Spector, Howard Barnum, Herbert J. Bernstein and Nikhil Swamy
 II. Theory
 II. Theory
 8. The Evolution of Size and Shape / William B. Langdon, Terry Soule, Riccardo Poli and James A. Foster
 9. Fitness Distributions: Tools for Designing Efficient Evolutionary Computations / Christian Igel and Kumar Chellapilla
 10. Analysis of SingleNode (Building) Blocks in Genetic Programming / Jason M. Daida, Robert R. Bertram, John A. Polito 2 and Stephen A. Stanhope
 11. RootedTree Schemata in Genetic Programming / Justinian P. Rosca and Dana H. Ballard
 III. Extensions
 III. Extensions
 12. Efficient Evolution of Machine Code for CISC Architectures Using Instruction Blocks and Homologous Crossover / Peter Nordin, Wolfgang Banzhaf and Frank D. Francone
 13. Submachinecode Genetic Programming / Riccardo Poli and William B. Langdon
 14. The Internal Reinforcement of Evolving Algorithms / Astro Teller
 15. Inductive Genetic Programming with Immune Network Dynamics / Nikolay I. Nikolaev, Hitoshi Iba and Vanio Slavov
 16. A SelfTuning Mechanism for DepthDependent Crossover / Takuyo Ito, Hitoshi Iba and Satoshi Sato
 17. Genetic Recursive Regression for Modeling and Forecasting RealWorld Chaotic Time Series / Geum Yong Lee
 18. Coevolutionary Fitness Switching: Learning Complex Collective Behaviors Using Genetic Programming / ByoungTak Zhang and DongYeon Cho
 19. Evolving Multiple Agents by Genetic Programming / Hitoshi Iba
 Index.
(source: Nielsen Book Data)
Genetic programming is a form of evolutionary computation that evolves programs and programlike executable structures for developing reliable time  and costeffective applications. It does this by breeding programs over many generations, using the principles of natural selection, sexual recombination, and mutuation. This third volume of "Advances in Genetic Programming" highlights many of the recent technical advances in this increasingly popular field.
(source: Nielsen Book Data)
 Cambridge, Mass. : MIT Press, ©1999.
 Description
 Book — 1 online resource (vii, 376 pages) : illustrations Digital: data file.
 Summary

 Introduction to support vector learning
 roadmap. Part 1 Theory: three remarks on the support vector method of function estimation, Vladimir Vapnik
 generalization performance of support vector machines and other pattern classifiers, Peter Bartlett and John ShaweTaylor
 Bayesian voting schemes and large margin classifiers, Nello Cristianini and John ShaweTaylor
 support vector machines, reproducing kernel Hilbert spaces, and randomized GACV, Grace Wahba
 geometry and invariance in kernel based methods, Christopher J.C. Burges
 on the annealed VC entropy for margin classifiers  a statistical mechanics study, Manfred Opper
 entropy numbers, operators and support vector kernels, Robert C. Williamson et al. Part 2 Implementations: solving the quadratic programming problem arising in support vector classification, Linda Kaufman
 making largescale support vector machine learning practical, Thorsten Joachims
 fast training of support vector machines using sequential minimal optimization, John C. Platt. Part 3 Applications: support vector machines for dynamic reconstruction of a chaotic system, Davide Mattera and Simon Haykin
 using support vector machines for time series prediction, KlausRobert Muller et al
 pairwise classification and support vector machines, Ulrich Kressel. Part 4 Extensions of the algorithm: reducing the runtime complexity in support vector machines, Edgar E. Osuna and Federico Girosi
 support vector regression with ANOVA decomposition kernels, Mark O. Stitson et al
 support vector density estimation, Jason Weston et al
 combining support vector and mathematical programming methods for classification, Bernhard Scholkopf et al.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
The Support Vector Machine is a powerful new learning algorithm for solving a variety of learning and function estimation problems, such as pattern recognition, regression estimation, and operator inversion. The impetus for this collection was a workshop on Support Vector Machines held at the 1997 NIPS conference. The contributors, both university researchers and engineers developing applications for the corporate world, form a Who's Who of this exciting new area.
(source: Nielsen Book Data)
46. Agents as objects with knowledge base state [1999]
 Skarmeas, Nikolaos.
 London : Imperial College Press ; River Edge, NJ : World Scientific [distributor], ©1999.
 Description
 Book — 1 online resource (xix, 274 pages) : illustrations
 Summary

 Introduction  background material
 the building blocks
 the April++ language  AprilO  adding objects to April
 AprilQ  the database extension
 April++  objects with knowledge base state
 the implementation of April++
 the applications  component based agent construction
 an agent for multiservice network management.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
47. Agents as objects with knowledge base state [1999]
 Skarmeas, Nikolaos.
 London : Imperial College Press ; River Edge, NJ : World Scientific [distributor], ©1999.
 Description
 Book — 1 online resource (xix, 274 pages) : illustrations
 Summary

 Introduction  background material
 the building blocks
 the April++ language  AprilO  adding objects to April
 AprilQ  the database extension
 April++  objects with knowledge base state
 the implementation of April++
 the applications  component based agent construction
 an agent for multiservice network management.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Lajoie, Susanne P.
 Amsterdam ; Washington, DC : IOS Press, ©1999.
 Description
 Book — 1 online resource (xv, 804 pages) : illustrations Digital: data file.
 Summary

 Machine generated contents note: Open Sesame?: Fifteen Variations on the Theme of Openness in Learning Environments / J. Self
 Cognitive Applications of New Computational Technologies in Eye Tracking / S.P. Marshall
 Collaborative Learning in Open Distributed Environments  Pedagogical Principles and Computational Methods / H.U. Hoppe
 Overview of the State of the Art in ITS Authoring Tools / T. Murray
 Trends and Issues in AI and Education: Towards a Common Research Framework / J. Sandberg
 Agent Systems for Diversity in Human Learning / J. Les / G. Cumming / S. Finch
 Teachable Agents: Combining Insights from Learning Theory and Computer Science / S. Brophy / G. Biswas / T. Katzlberger / [and others]
 Metaknowledge Representation for Learning Scenarios Engineering / G. Paquette
 MultiAgent Design of a PeerHelp Environment / J. Vassileva / J. Greer / G. McCalla / [and others]
 Methodology for Building Intelligent Educational Agents / H.N. Keeling
 Systemion: A New Agent Model to Design Intelligent Tutoring Systems / M.F. Canut / G. Gouarderes / E. Sanchis
 Learning Goal Ontology Supported by Learning Theories for Opportunistic Group Formation / T. Supnithi / A. Inaba / M. Ikeda / [and others]
 Toward Intelligent Analysis and Support of Collaborative Learning Interaction / A. Soller / F. Linton / B. Goodman / [and others]
 OntologyAware Authoring Tool: Functional Structure and Guidance Generation / L. Jin / W. Chen / Y. Hayashi / [and others]
 Formatively Evaluating REDEEM  An Authoring Environment for ITSs / S. Ainsworth / J. Underwood / S. Grimshaw
 Intelligent Agent Instructional Design Tool for a Hypermedia Design Course / S. Stoyanov / L. Aroyo / P. Kommers.
 Brooks, Rodney Allen.
 Cambridge, Mass. : MIT Press, ©1999.
 Description
 Book — 1 online resource (xii, 199 pages) : illustrations
 Summary

 pt. I. Technology. Robust layered control system for a mobile robot
 Robot that walks: emergent behaviors from a carefully evolved network
 Learning a distributed map representation based on navigation behaviors
 New approaches to robotics. pt. II. Philosophy. Intelligence without representation
 Planning is just a way of avoiding figuring out what to do next
 Elephants don't play chess
 Intelligence without reason.
(source: Nielsen Book Data)
 Singapore ; New Jersey : World Scientific, ©1999.
 Description
 Book — 1 online resource (xiv, 360 pages) : illustrations
 Summary

 An introduction to evolutionary computation
 evolutionary algorithms as search algorithms
 theoretical analysis of evolutionary algorithms
 advanced search operators in evolutionary algorithms
 parallel evolutionary algorithms
 a comparison of simulated annealing and an evolutionary algorithm on traveling salesman problems
 power system design and management by evolutionary algorithms
 telecommunications network design and management by evolutionary algorithms
 an optimization tool based on evolutionary algorithms
 the evolution of artificial neural network architectures
 an experimental study of generalization in evolutionary learning
 an evolutionary approach to the Nperson prisoner's dilemma game
 automated design and generalisation of heuristics
 highorder credit assignment in classifier systems.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
51. Shape recognition [1999]
 Exeter, Eng. : Intellect, ©1999.
 Description
 Book — 1 online resource (235 pages) : illustrations
 Summary

 Cortical images, selforganising neural networks and object classification / Nikolay Petkov
 Parallel implementation of a neural network ensemble on the connection machine / Daijin Kim, Minsoo Suk
 Boolean neural networks trained with simulated annealing / Jarkko Niittylahti
 On the computational complexity of analyzing the HopfieldClique network / Arun Jagota
 A harmonymaximisation network implementation of a compound labeling scheme for scene analysis / Tatiana Tambouratzis
 Optimal image boundary via Hopfield net and tunneling / William Cheung, Roland Chin, Tong Lee
 Shape matching based on invariants / Stan Z. Li.
 Singapore ; River Edge, N.J. : World Scientific, ©1999.
 Description
 Book — 1 online resource (xxv, 479 pages) : illustrations
 Summary

 Neural networks in systems identification and control  supervised learning in multilayer perceptions  the backpropagation algorithm
 identification of twodimensional state space discrete systems using neural networks
 neural networks for control
 neurobased adaptive regulator
 local model networks and selftuning predictive control
 fuzzy and neurofuzzy systems in modelling, control and robot path planning  an online self constructing fuzzy modelling architecture based on neural and fuzzy concepts and techniques
 neurofuzzy modelbased control
 fuzzy and neurofuzzy approaches to mobile robot path and motion planning under uncertainty
 geneticevolutionary algorithms  a tutorial overview of genetic algorithms and their applications
 results from a variety of genetic algorithm applications showing the robustness of the approach
 evolutionary algorithms in computeraided design of integrated circuits
 soft computing applications  soft data fusion
 application of neural networks to computer gaming
 coherent neural networks and their applications to control and signal processing
 neural, fuzzy and evolutionary reinforcement learning systems  an application case study
 neural networks in industrial and environmental applications.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Bonabeau, Eric.
 New York : Oxford University Press, 1999.
 Description
 Book — 1 online resource (xii, 307 pages) : illustrations Digital: data file.
 Summary

 Ch. 1. Introduction
 Ch. 2. Ant Foraging Behavior, Combinatorial Optimization, and Routing in Communications Network
 Ch. 3. Division of Labor and Task Allocation
 Ch. 4. Cemetery Organization, Brood Sorting, Data Analysis, and Graph Partitioning
 Ch. 5. SelfOrganization and Templates: Application to Data Analysis and Graph Partitioning
 Ch. 6. Nest Building and SelfAssembling
 Ch. 7. Cooperative Transport by Insects and Robots
 Ch. 8. Epilogue.
(source: Nielsen Book Data)
54. Understanding intelligence [1999]
 Pfeifer, Rolf, 1947
 Cambridge, Mass. : MIT Press, ©1999.
 Description
 Book — 1 online resource (xx, 697 pages) : illustrations Digital: data file.
 Summary

 The Study of IntelligenceFoundations and Issues
 The Study of Intelligence
 Characterizing Intelligence
 Studying Intelligence: The Synthetic Approach
 Foundations of Classical Artificial Intelligence and Cognitive Science
 Cognitive Science: Preliminaries
 The Cognitivistic Paradigm
 An Architecture for an Intelligent Agent
 The Fundamental Problems of Classical Al and Cognitive Science
 Real Worlds versus Virtual Worlds
 Some WellKnown Problems with Classical Systems
 The Fundamental Problems of Classical Al
 Remedies and Alternatives
 A Framework for Embodied Cognitive Science
 Embodied Cognitive Science: Basic Concepts
 Complete Autonomous Agents
 Biological and Artificial Agents
 Designing for EmergenceLogicBased and Embodied Systems
 Explaining Behavior
 Neural Networks for Adaptive Behavior
 From Biological to Artificial Neural Networks
 The Four or Five Basics
 Distributed Adaptive Control
 Types of Neural Networks
 Beyond Information Processing: A Polemic Digression
 Approaches and Agent Examples
 Braitenberg Vehicles
 Motivation
 The Fourteen Vehicles
 Segmentation of Behavior and the Extended Braitenberg Architecture
 The Subsumption Architecture
 BehaviorBased Robotics
 Designing a SubsumptionBased Robot
 Examples of SubsumptionBased Architectures
 Conclusions: The Subsumption Approach to Designing Intelligent Systems
 Artificial Evolution and Artificial Life.
(source: Nielsen Book Data)
Evolutionary theory says that the brain has evolved not to do mathematical proofs but to control behaviour and ensure survival. Researchers agree that intelligence always manifests itself in behaviour  thus it is behaviour that must be understood. A new field has grown around the study of behaviourbased intelligence, also known as embodied cognitive science, "new AI" and "behaviourbased AI". This book provides a systematic introduction to this new way of thinking. After discussing concepts and approaches such as subsumption architecture, Braitenberg vehicles, evolutionary robotics, artificial life, selforganization and learning, the authors derive a set of principles and a framework for the study of naturally and artificially intelligent systems, or autonomous agents. This framework is based on a synthetic methodology whose goal is understanding by designing and building. The text includes the background material required to understand the principles underlying intelligence, as well as information of intelligent robotics and simulated agents so readers can begin experiments and projects on their own. The reader is guided through a series of case studies that illustrate the design principles of embodied cognitive science.
(source: Nielsen Book Data)
 Pfeifer, Rolf, 1947
 Cambridge, Mass. : MIT Press, ©1999.
 Description
 Book — 1 online resource (xx, 697 pages) : illustrations
 Summary

 The Study of IntelligenceFoundations and Issues
 The Study of Intelligence
 Characterizing Intelligence
 Studying Intelligence: The Synthetic Approach
 Foundations of Classical Artificial Intelligence and Cognitive Science
 Cognitive Science: Preliminaries
 The Cognitivistic Paradigm
 An Architecture for an Intelligent Agent
 The Fundamental Problems of Classical Al and Cognitive Science
 Real Worlds versus Virtual Worlds
 Some WellKnown Problems with Classical Systems
 The Fundamental Problems of Classical Al
 Remedies and Alternatives
 A Framework for Embodied Cognitive Science
 Embodied Cognitive Science: Basic Concepts
 Complete Autonomous Agents
 Biological and Artificial Agents
 Designing for EmergenceLogicBased and Embodied Systems
 Explaining Behavior
 Neural Networks for Adaptive Behavior
 From Biological to Artificial Neural Networks
 The Four or Five Basics
 Distributed Adaptive Control
 Types of Neural Networks
 Beyond Information Processing: A Polemic Digression
 Approaches and Agent Examples
 Braitenberg Vehicles
 Motivation
 The Fourteen Vehicles
 Segmentation of Behavior and the Extended Braitenberg Architecture
 The Subsumption Architecture
 BehaviorBased Robotics
 Designing a SubsumptionBased Robot
 Examples of SubsumptionBased Architectures
 Conclusions: The Subsumption Approach to Designing Intelligent Systems
 Artificial Evolution and Artificial Life.
(source: Nielsen Book Data)
By the mid1980s researchers from artificial intelligence, computer science, brain and cognitive science, and psychology realized that the idea of computers as intelligent machines was inappropriate. The brain does not run "programs"; it does something entirely different. But what? Evolutionary theory says that the brain has evolved not to do mathematical proofs but to control our behavior, to ensure our survival. Researchers now agree that intelligence always manifests itself in behaviorthus it is behavior that we must understand. An exciting new field has grown around the study of behaviorbased intelligence, also known as embodied cognitive science, "new AI, " and "behaviorbased AI."This book provides a systematic introduction to this new way of thinking. After discussing concepts and approaches such as subsumption architecture, Braitenberg vehicles, evolutionary robotics, artificial life, selforganization, and learning, the authors derive a set of principles and a coherent framework for the study of naturally and artificially intelligent systems, or autonomous agents. This framework is based on a synthetic methodology whose goal is understanding by designing and building.The book includes all the background material required to understand the principles underlying intelligence, as well as enough detailed information on intelligent robotics and simulated agents so readers can begin experiments and projects on their own. The reader is guided through a series of case studies that illustrate the design principles of embodied cognitive science.
(source: Nielsen Book Data)
 Pfeifer, Rolf, 1947
 Cambridge, Mass. : MIT Press, ©1999.
 Description
 Book — 1 online resource (xx, 697 pages) : illustrations
 Summary

 The Study of IntelligenceFoundations and Issues
 The Study of Intelligence
 Characterizing Intelligence
 Studying Intelligence: The Synthetic Approach
 Foundations of Classical Artificial Intelligence and Cognitive Science
 Cognitive Science: Preliminaries
 The Cognitivistic Paradigm
 An Architecture for an Intelligent Agent
 The Fundamental Problems of Classical Al and Cognitive Science
 Real Worlds versus Virtual Worlds
 Some WellKnown Problems with Classical Systems
 The Fundamental Problems of Classical Al
 Remedies and Alternatives
 A Framework for Embodied Cognitive Science
 Embodied Cognitive Science: Basic Concepts
 Complete Autonomous Agents
 Biological and Artificial Agents
 Designing for EmergenceLogicBased and Embodied Systems
 Explaining Behavior
 Neural Networks for Adaptive Behavior
 From Biological to Artificial Neural Networks
 The Four or Five Basics
 Distributed Adaptive Control
 Types of Neural Networks
 Beyond Information Processing: A Polemic Digression
 Approaches and Agent Examples
 Braitenberg Vehicles
 Motivation
 The Fourteen Vehicles
 Segmentation of Behavior and the Extended Braitenberg Architecture
 The Subsumption Architecture
 BehaviorBased Robotics
 Designing a SubsumptionBased Robot
 Examples of SubsumptionBased Architectures
 Conclusions: The Subsumption Approach to Designing Intelligent Systems
 Artificial Evolution and Artificial Life.
(source: Nielsen Book Data)
By the mid1980s researchers from artificial intelligence, computer science, brain and cognitive science, and psychology realized that the idea of computers as intelligent machines was inappropriate. The brain does not run "programs"; it does something entirely different. But what? Evolutionary theory says that the brain has evolved not to do mathematical proofs but to control our behavior, to ensure our survival. Researchers now agree that intelligence always manifests itself in behaviorthus it is behavior that we must understand. An exciting new field has grown around the study of behaviorbased intelligence, also known as embodied cognitive science, "new AI, " and "behaviorbased AI."This book provides a systematic introduction to this new way of thinking. After discussing concepts and approaches such as subsumption architecture, Braitenberg vehicles, evolutionary robotics, artificial life, selforganization, and learning, the authors derive a set of principles and a coherent framework for the study of naturally and artificially intelligent systems, or autonomous agents. This framework is based on a synthetic methodology whose goal is understanding by designing and building.The book includes all the background material required to understand the principles underlying intelligence, as well as enough detailed information on intelligent robotics and simulated agents so readers can begin experiments and projects on their own. The reader is guided through a series of case studies that illustrate the design principles of embodied cognitive science.
(source: Nielsen Book Data)
57. Advances in large margin classifiers [2000]
 Cambridge, Mass. : MIT Press, ©2000.
 Description
 Book — 1 online resource (vi, 412 pages) : illustrations
 Summary

The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classificationthat is, a scale parameterrather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.
(source: Nielsen Book Data)
 Cambridge, Mass. : MIT Press, ©2000.
 Description
 Book — 1 online resource (vi, 412 pages) : illustrations.
 Summary

The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classificationthat is, a scale parameterrather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.
(source: Nielsen Book Data)
 Cambridge, Mass. : MIT Press, ©2000.
 Description
 Book — 1 online resource (vi, 412 pages) : illustrations.
 Summary

The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classificationthat is, a scale parameterrather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.
(source: Nielsen Book Data)
60. Conceptual spaces : the geometry of thought [2000]
 Gärdenfors, Peter.
 Cambridge, Mass. : MIT Press, ©2000.
 Description
 Book — 1 online resource (x, 307 pages) : illustrations Digital: data file.
 Summary

 1. Dimensions
 2. Symbolic, conceptual, and subconceptual representations
 3. Properties
 4. Concepts
 5. Semantics
 6. Induction
 7. Computational aspects
 8. In Chase of Space.
(source: Nielsen Book Data)
61. Embodied conversational agents [2000]
 Cambridge, Mass. : MIT Press, ©2000.
 Description
 Book — 1 online resource (430 pages) : illustrations Digital: data file.
 Summary

 I. Introduction
 1. Nudge Nudge Wink Wink: Elements of FacetoFace Conversation for Embodied Conversation Agents / Justine Cassell
 II. Systems
 2. Human Conversation as a System Framework: Designing Embodied Conversational Agents / Justine Cassell, Tim Bickmore and Lee Campbell / [and others]
 3. "May I Help You?": Designing Embodied Conversational Agent Allies / Elizabeth F. Churchill, Linda Cook and Peter Hodgson / [and others]
 4. TaskOriented Collaboration with Embodied Agents in Virtual Worlds / Jeff Rickel and W. Lewis Johnson
 5. Deictic and Emotive Communication in Animated Pedagogical Agents / James C. Lester, Stuart G. Towns and Charles B. Callaway / [and others]
 6. Performative Facial Expressions in Animated Faces / Isabella Poggi and Catherine Pelachaud
 7. Emotion and Personality in a Conversational Agent / Gene Ball and Jack Breese
 8. The Automated Design of Believable Dialogues for Animated Presentation Teams / Elisabeth Andre, Thomas Rist and Susanne van Mulken / [and others]
 9. Parameterized Action Representation for Virtual Human Agents / Norman I. Badler, Rama Bindiganavale and Jan Allbeck / [and others]
 III. Evaluation
 10. Developing and Evaluating Conversational Agents / Dominic W. Massaro, Michael M. Cohen and Jonas Beskow / [and others]
 11. Designing and Evaluating Conversational Interfaces with Animated Characters / Sharon Oviatt and Bridget Adams
 12. Measurement and Evaluation of Embodied Conversational Agents / Greogry A. Sanders and Jean Scholtz
 13. Truth Is Beauty: Researching Embodied Conversational Agents / Clifford Nass, Katherine Isbister and EunJu Lee.
(source: Nielsen Book Data)
62. Heterogeneous agent systems [2000]
 Cambridge, Mass. : MIT Press, ©2000.
 Description
 Book — 1 online resource (xiv, 580 pages) : illustrations
 Summary

 1. Introduction
 2. IMPACT architecture
 3. service description language
 4. Accessing legacy data and software
 5. IMPACT server implementation
 6. Agent programs
 7. Meta agent programs
 8. Temporal agent programs
 9. Probabilistic agent programs
 10. Secure agent programs
 11. Complexity results
 12. Implementing agents
 13. An example application
 14. Conclusions.
(source: Nielsen Book Data)
 Cristianini, Nello.
 Cambridge ; New York : Cambridge University Press, 2000.
 Description
 Book — 1 online resource (xiii, 189 pages) : illustrations (some color)
 Summary

 Preface
 1. The learning methodology
 2. Linear learning machines
 3. Kernelinduced feature spaces
 4. Generalisation theory
 5. Optimisation theory
 6. Support vector machines
 7. Implementation techniques
 8. Applications of support vector machines
 Appendix A: pseudocode for the SMO algorithm
 Appendix B: background mathematics
 Appendix C: glossary
 Appendix D: notation
 Bibliography
 Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Stone, Peter, 1971 author.
 Cambridge, Massachusetts : MIT Press, [2000]
 Description
 Book — 1 online resource (xii, 272 pages) : illustrations
 Summary

 Introduction
 Substrate systems
 Team member agent architecture
 Layered learning
 Learning an individual skill
 Learning a multiagent behavior
 Learning a team behavior
 Competition results
 Related work
 Conclusions and future work.
(source: Nielsen Book Data)
65. Reasoning about rational agents [2000]
 Wooldridge, Michael J., 1966
 Cambridge, Mass. : MIT Press, 2000.
 Description
 Book — 1 online resource (xi, 227 pages)
 Summary

 1. Rational Agents
 2. The BeliefDesireIntention Model
 3. Introduction to LORA
 4. LORA Defined
 5. Properties of Rational Agents
 6. Collective Mental States
 7. Communication
 8. Cooperation
 9. Logic and Agent Theory.
(source: Nielsen Book Data)
 San Diego : Academic Press, ©2000.
 Description
 Book — 1 online resource (xvii, 639 pages) : illustrations
 Summary

 Outline of a computational theory of perceptions based on computing with words / L.A. Zadeh
 Introduction to soft computing and intelligent control systems / N.K. Sinha and M.M. Gupta
 Computational issues in intelligent control / X.D. Koutsoukos and P.J. Antsaklis
 Neural networks
 a guided tour / S. Haykin
 On generating variable structure organization using a genetic algorithm / A.K. Zaidi and A.H. Levis
 Evolutionary algorithms and neural networks / R.G.S. Asthana
 Neural networks and fuzzy systems / P. Musilek and M.M. Gupta
 Fuzzy neural networks / P. Musilek and M.M. Gupta
 A cursory look at parallel and distributed architectures and biologically inspired computing / S.K. Basu
 Developments in learning control systems / J.X. Xu [and others]
 Techniques for genetic adaptive control / W.K. Lennon and K.M. Passino
 Cooperative behavior of intelligent agents : theory and practice / L. Vlacic, A. Engwirda, and M. Kajitani
 Expert systems in process diagnosis and control / D. Popovic
 Neural networks for identification of nonlinear systems : an overview / P. Gupta and N.K. Sinha
 Sensor fusion system using recurrent fuzzy inference / F. Kobayashi [and others]
 Neurofuzzy state estimators / C.J. Harris, X. Hong, and Q. Gan.
 Soft computing paradigms for artificial vision / K.K. Shukla
 Intelligent control with neural networks / D. Popovic
 Knowledgebased adaptation of neurofuzzy models in predictive control of a heat exchanger / M. Fischer, O. Nelles, and R. Isermann
 Neural network approximation of piecewise continuous functions : application to friction compensation / R.R. Selmic and F.L. Lewis
 Fuzzy adaptive and predictive control of a thermic process / I. Skrjanc and D. Matko
 An intelligent approach to positive target identification / R.N.P. Singh
 Adaptive agents and artificial life : insights for the power industry / S.A. Harp and T. Samad
 Truck backerupper control using dynamic neural network / M.M Gupta and D.H. Rao
 Toward intelligent machines : future perspectives / M.M. Gupta and N.K. Sinha.
(source: Nielsen Book Data)
67. Truth from trash : how learning makes sense [2000]
 Thornton, Christopher James.
 Cambridge, MA : MIT Press, ©2000.
 Description
 Book — 1 online resource (x, 204 pages) : illustrations
 Summary

 Preface
 1. The Machine That Could Learn Anything
 2. Consider Thy Neighbor
 3. Kepler on Mars
 4. The Information Chicane
 5. FenceandFill Learning
 6. Turing and the Submarines
 7. The Relational Gulf
 8. The Supercharged Learner
 9. David Hume and the Crash of '87
 10. Phases of Compression
 11. Protorepresentational Learning
 12. The Creativity Continuum
 References
 Index.
(source: Nielsen Book Data)
 Singapore ; River Edge, NJ : World Scientific, ©2001.
 Description
 Book — 1 online resource (x, 298 pages) : illustrations, portraits
 Summary

 1. Speech hyphenation segmentation by means of blind source separation / Harold Szu and Charles Hsu
 2. Higherorder moments based synthesis of supervised fourier demixing filter / Eiji Uchino, Noriaki Suetake, and Takeshi Yamakawa
 3. Design and application of an acoustic database navigator for the intractive analysis of psychoacoustic sound archives and sound engineerint / Andreas Konig, Friedrich E. Blutner, Michael Eberhardt, and Robert Wenzel
 4. Multilayer perceptron networks with adaptive centroid transformation / Mikko Lehtokangas
 5. Identification and analysis for transiently evoked otoacoustic emission / Liming Li, Jinsen Lin, and Zhengguo Zhang
 6. New reliability models based on imprecise probabilities / Lev V. Utkin and Sergey V. Gurov.
 7. Multimodular neural network for breast cancer detection / Huai Li and K.J. Ray Liu
 8. Advanced neural nets for visual image communication / Harold Szu and Charles Hsu
 9. Continuous valued techniques based on the Lagrangian method for the wire routing problem / Shakeel Ismail, Masahiro Nagamatu and Torao Yanaru
 10. Chaotic neural networks for information processing / Charles Hsu and Harold Szu
 11. Wavelet encoding for interactive genetic algorithm in emotional image retrieval / JooYoung Lee and SungBae Cho
 12. Call admission control using interval arithmetic coulomb energy network / Won Don Lee, Kyunghee Lee and Hongkee Kim.
(source: Nielsen Book Data)
 Patel, Mukesh.
 Cambridge, Mass. : MIT Press, 2001.
 Description
 Book — 1 online resource (xxiv, 480 pages) : illustrations
 Summary

 1. Evolutionary and neural synthesis of intelligent agents / by Karthik Balakrishnan and Vasant Honavar
 2. Cellular encoding for interactive evolutionary robotics / by Frédéric Gruau and Kameel Quatramaran
 3. The emergence of communication through synthetic evolution / by Bruce J. MacLennan
 4. Optimization of classifiers using genetic algorithms / by J.J. Merelo, A. Prieto and F. Morán
 5. Evolving neurocontrollers and sensors for artificial agents / by Karthik Balakrishnan and Vasant Honavar
 6. Combined biological metaphors / by Egbert J.W. Boers and Ida G. SprinkhuizenKuyper
 7. Evolutionary neurogenesis applied to mobile robotics / by Oliver Michel
 8. Development in neural networks / by Domenico Parisi and Stefano Nolfi
 9. Evolution and learning in radial basis function neural networks : a hybrid approach / by Brian Carse, Terence C. Fogarty and John C.W. Sullivan
 10. Coevolution and ontogenetic change in competing robots / by Dario Floreano, Stefano Nolfi and Francesco Mondada
 11. Goal directed adaptive behavior in secondorder neural networks : learning and evolving in the MAXSON architecture / by Federick L. Crabbe and Michael G. Dyer
 12. Evolving heterogeneous neural agents by local selection / by Filippo Menczer, W. Nick Street and Melania Degeratu
 13. Learning sequential decision tasks through symbiotic evolution of neural networks / by David E. Moriarty and Risto Miikkulainen
 14. From evolving a single neural network to evolving neural network ensembles / by Xin Yao and Yong Liu
 15. Evolutionary synthesis of Bayesian networks for optimization / by Heinz Mühlenbein and Thilo Mahnig.
(source: Nielsen Book Data)
70. Agent engineering [2001]
 Singapore ; River Edge, N.J. : World Scientific, ©2001.
 Description
 Book — 1 online resource (viii, 265 pages) : illustrations Digital: data file.
 Summary

 Introduction to agent engineering, J.M. Liu et al
 why autonomy makes the agent, S. Joseph and T. Kawamura
 knowledge granularity spectrum, action pyramid and the scaling problem, Y.M. Ye and J.K. Tsotsos
 the motivation for dynamic decisionmaking frameworks in multiagent systems, K.S. Barber and C.E. Martin
 dynamically organizing KDD processes in a multiagent KDD system, N. Zhong et al
 selforganized intelligence, J.M. Liu
 valuationbased coalition formation in multiagent systems, S.J. Johansson
 simulating how to cooperate in iterated chicken and prisoner's dilemma games, B. Carlsson
 training intelligent agents using human data collected on the Internet, E. Sklar et al
 agent dynamics  soap paradigm, F.W.K. Lor.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
71. Agent engineering [electronic resource] [2001]
 Singapore ; River Edge, N.J. : World Scientific, c2001.
 Description
 Book — 1 online resource (viii, 265 p.) : ill.
 Summary

 Introduction to agent engineering, J.M. Liu et al
 why autonomy makes the agent, S. Joseph and T. Kawamura
 knowledge granularity spectrum, action pyramid and the scaling problem, Y.M. Ye and J.K. Tsotsos
 the motivation for dynamic decisionmaking frameworks in multiagent systems, K.S. Barber and C.E. Martin
 dynamically organizing KDD processes in a multiagent KDD system, N. Zhong et al
 selforganized intelligence, J.M. Liu
 valuationbased coalition formation in multiagent systems, S.J. Johansson
 simulating how to cooperate in iterated chicken and prisoner's dilemma games, B. Carlsson
 training intelligent agents using human data collected on the Internet, E. Sklar et al
 agent dynamics  soap paradigm, F.W.K. Lor.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Liu, Jiming, 1962
 Singapore ; River Edge, N.J. : World Scientific, 2001.
 Description
 Book — 1 online resource (xx, 280 p.) : ill.
 Summary

 Behavioural modelling, planning, and learning
 synthetic autonomy
 dynamics of distributed computation
 selforganized autonomy in multiagent systems
 autonomyoriented computation
 dynamics and complexity of autonomyoriented computation.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Liu, Jiming, 1962
 Singapore ; River Edge, N.J. : World Scientific, 2001.
 Description
 Book — 1 online resource (xx, 280 pages) : illustrations Digital: data file.
 Summary

 Behavioural modelling, planning, and learning
 synthetic autonomy
 dynamics of distributed computation
 selforganized autonomy in multiagent systems
 autonomyoriented computation
 dynamics and complexity of autonomyoriented computation.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
74. Foundations of genetic algorithms 6 [2001]
 San Francisco, Calif. : Morgan Kaufmann, ©2001.
 Description
 Book — 1 online resource (342 pages) : illustrations
 Summary

 Front Cover; Foundations of Genetic Algorithms6; Copyright Page; Contents;
 Chapter 1. Introduction;
 Chapter 2. Overcoming Fitness Barriers in MultiModal Search Spaces;
 Chapter 3. Niches in NKLandscapes;
 Chapter 4. New Methods for Tunable, Random Landscapes;
 Chapter 5. Analysis of Recombinative Algorithms on a NonSeparable BuildingBlock Problem;
 Chapter 6. Direct Statistical Estimation of GA Landscape Properties;
 Chapter 7. Comparing Population Mean Curves;
 Chapter 8. Local Performance of the ((/(I, () ES in a Noisy Environment
 Chapter 9. Recursive Conditional Scheme Theorem, Convergence and Population Sizing in Genetic Algorithms
 Chapter 10. Towards a Theory of Strong Overgeneral Classifiers;
 Chapter 11. Evolutionary Optimization through PAC Learning;
 Chapter 12. Continuous Dynamical System Models of SteadyState Genetic Algorithms;
 Chapter 13. MutationSelection Algorithm: A Large Deviation Approach;
 Chapter 14. The Equilibrium and Transient Behavior of Mutation and Recombination;
 Chapter 15. The Mixing Rate of Different Crossover Operators;
 Chapter 16. Dynamic Parameter Control in Simple Evolutionary Algorithms
 Chapter 17. Local Search and High Precision Gray Codes: Convergence Results and Neighborhoods
 Chapter 18. Burden and Benefits of Redundancy; Author Index; Key Word Index
 Principia evolvica. English
 Jacob, Christian.
 San Francisco : Morgan Kaufmann Pub., ©2001.
 Description
 Book — 1 online resource (xvii, 578 pages) : illustrations Digital: text file.
 Summary

 Part 1: Fascinating Evolution
 Part 2: Evolutionary Computation
 Part 3: If Darwin was a Programmer
 Part 4: Evolution of Developmental Programs.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 AsiaPacific Conference on Intelligent Agent Technology (2nd : 2001 : Maebashi, Japan)
 River Edge, N.J. : World Scientific, 2001.
 Description
 Book — 1 online resource (xiii, 517 pages) : illustrations
 Summary

 Formal Agent Theoreis
 Computational Architecture and Infrastructure
 Learning and Adaptation
 Knowledge Discovery and Data Mining Agents
 Distributed Intelligence
 Agent Based Applications.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
77. Microsoft data mining : integrated business intelligence for eCommerce and knowledge management [2001]
 De Ville, Barry.
 Boston : Digital Press, ©2001.
 Description
 Book — 1 online resource (xx, 315) : illustrations
 Summary

 Introduction to Data Mining
 The Data Mining Process
 Data Mining Tools and Techniques
 Managing the Data Mining Project
 Modeling Data
 Deploying the Results
 The Discovery and Delivery of Knowledge for Effective Enterprise Outcomes: Knowledge Management
 Appendices: Glossary
 References
 Web Sites
 Data Mining and Knowledge Discovery Data Sets in the Public Domain
 Microsoft Solution Providers
 Summary of Knowledge Management Case Studies and Web Locations.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Singapore ; River Edge, NJ : World Scientific, ©2001.
 Description
 Book — 1 online resource (xiv, 374 pages) : illustrations
 Summary

 Knowledge engineering and soft computing  an introduction, L.Y. Ding. Part 1 Fuzzy knowledgebased systems: linguistic integrity  a framework for fuzzy modelling, AFRELI algorithm, J. Espinosa and J. Vandewalle
 a new approach to acquisition of comprehensible fuzzy rules, H. Ohno and T. Furuhashi
 fuzzy rule generation with fuzzy singletontype reasoning method, Y. Shi and M. Mizumoto
 antecedent validity adaptation principle for table lookup scheme, P.T. Chan and A.B. Rad
 fuzzy spline interpolation in sparse fuzzy rule bases, M.F. Kawaguchi and M. Miyakoshi
 revision principles applied for approximate reasoning, L.Y. Ding et al
 handling null queries with compound fuzzy attributes, S.L. Wang and Y.J. Tsai
 fuzzy system description language, K. Otsuka et al. Part 2 Knowledge representation, integration and discovery by soft computing: knowledge representation and similarity measures in learning a vague legal concept, M.Q. Xu et al
 trend fuzzy sets and recurrent fuzzy rules for ordered dataset modelling, J.F. Baldwin et al
 approaches to the design of classification systems from numerical data and linguistic knowledge, H. Ishibuchi et al
 a clustering based on selforganizing map and knowledge discovery by neural network, K. Nakagawa et al
 probabilistic rough induction, J.Z. Dong et al
 data mining via linguistic summaries of databases  an interactive approach, J. Kacprzyk and S. Zadrozny. (Part contents).
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Singapore ; River Edge, NJ : World Scientific, c2001.
 Description
 Book — 1 online resource (xiv, 374 p.) : ill.
 Summary

 Knowledge engineering and soft computing  an introduction, L.Y. Ding. Part 1 Fuzzy knowledgebased systems: linguistic integrity  a framework for fuzzy modelling, AFRELI algorithm, J. Espinosa and J. Vandewalle
 a new approach to acquisition of comprehensible fuzzy rules, H. Ohno and T. Furuhashi
 fuzzy rule generation with fuzzy singletontype reasoning method, Y. Shi and M. Mizumoto
 antecedent validity adaptation principle for table lookup scheme, P.T. Chan and A.B. Rad
 fuzzy spline interpolation in sparse fuzzy rule bases, M.F. Kawaguchi and M. Miyakoshi
 revision principles applied for approximate reasoning, L.Y. Ding et al
 handling null queries with compound fuzzy attributes, S.L. Wang and Y.J. Tsai
 fuzzy system description language, K. Otsuka et al. Part 2 Knowledge representation, integration and discovery by soft computing: knowledge representation and similarity measures in learning a vague legal concept, M.Q. Xu et al
 trend fuzzy sets and recurrent fuzzy rules for ordered dataset modelling, J.F. Baldwin et al
 approaches to the design of classification systems from numerical data and linguistic knowledge, H. Ishibuchi et al
 a clustering based on selforganizing map and knowledge discovery by neural network, K. Nakagawa et al
 probabilistic rough induction, J.Z. Dong et al
 data mining via linguistic summaries of databases  an interactive approach, J. Kacprzyk and S. Zadrozny. (Part contents).
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Singapore ; River Edge, NJ : World Scientific, ©2001.
 Description
 Book — 1 online resource (xiii, 424 pages) : illustrations
 Summary

 Automatic detection of microcalcifications in mammograms using a fuzzy classifier, A.P. Drijarkara et al
 predictive fuzzy model for control of an artificial muscle, P.B. Petrovi
 evolutionary computation for information retrieval based on user preference, H.G. Kim and S.B. Cho
 fuzzy logic and neural networks approach  a way to improve overall performance of integrated heating systems, E. Entchev
 design and tuning a neurofuzzy power system stabilizer using genetic algorithms, A. Afzalian and D.A. Linkens
 an application of logic programmes with soft computing aspects to fault diagnosis in digital circuits, H. Sakai et al
 determination of the motion parameters from the perspective projection of a triangle, M.M. Sein and H. Hama. (Part contents).
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
81. Statistical mechanics of learning [2001]
 Engel, A. (Andreas), 1957
 Cambridge, UK ; New York, NY : Cambridge University Press, 2001.
 Description
 Book — 1 online resource (xi, 329 pages) : illustrations
 Summary

 Getting started
 Perceptron learning  basics
 Choice of learning rules
 Augmented statistical mechanics formulation
 Noisy teachers
 Storage problem
 Discontinuous learning
 Unsupervised learning
 Online learning
 Making contact with statistics
 Bird's eye view: multifractals
 Multilayer networks
 Online learning in multilayer networks
 What else?
(source: Nielsen Book Data)
 Kraus, Sarit.
 Cambridge, Mass. : MIT Press, ©2001.
 Description
 Book — 1 online resource (xiv, 266 pages) : illustrations
 Summary

 1. Introduction
 2. The strategicnegotiation model
 3. Negotiations about data allocation
 4. Negotiations about resource allocation
 5. Negotiations about resource allocation with multiple attributes
 6. Negotiations about task distribution
 7. Negotiations about how to reduce pollution
 8. Negotiation during a hostage crisis
 9. Economic and gametheoretic models for cooperation
 10. Conclusions and future directions.
(source: Nielsen Book Data)
83. Understanding intelligence [2001]
 Pfeifer, Rolf, 1947
 Cambridge, Massachusetts : MIT Press, c1999 [Piscataqay, New Jersey] : IEEE Xplore, [2001]
 Description
 Book — 1 online resource (xx, 697 pages) : illustrations
 Summary

The book includes all the background material required to understand the principles underlying intelligence, as well as enough detailed information on intelligent robotics and simulated agents so readers can begin experiments and projects on their own. By the mid1980s researchers from artificial intelligence, computer science, brain and cognitive science, and psychology realized that the idea of computers as intelligent machines was inappropriate. The brain does not run "programs"; it does something entirely different. But what? Evolutionary theory says that the brain has evolved not to do mathematical proofs but to control our behavior, to ensure our survival. Researchers now agree that intelligence always manifests itself in behaviorthus it is behavior that we must understand. An exciting new field has grown around the study of behaviorbased intelligence, also known as embodied cognitive science, "new AI, " and "behaviorbased AI." This book provides a systematic introduction to this new way of thinking. After discussing concepts and approaches such as subsumption architecture, Braitenberg vehicles, evolutionary robotics, artificial life, selforganization, and learning, the authors derive a set of principles and a coherent framework for the study of naturally and artificially intelligent systems, or autonomous agents. This framework is based on a synthetic methodology whose goal is understanding by designing and building. The book includes all the background material required to understand the principles underlying intelligence, as well as enough detailed information on intelligent robotics and simulated agents so readers can begin experiments and projects on their own. The reader is guided through a series of case studies that illustrate the design principles of embodied cognitive science.
(source: Nielsen Book Data)
 Singapore ; River Edge, NJ : World Scientific, c2001.
 Description
 Book — 1 online resource (xii, 309 p.) : ill.
 Summary

 Consideration of emotion model and primitive language of robots, T. Ogata and S. Sugano
 an architecture for animallike behaviour selection, T. Kitamura
 a computation literary theory the ultimate products of the brain/mind machine, A. Tokosumi
 cooperation between neural networks within the brain, M. Dufosse et al
 brainlike functions in evolving connectionist systems for online, knowledgebased learning, N. Kasabov
 interrelationships, communication, semiotics and artificial consciousness, H.N.L. Teodorescu
 time emerges from incomplete clock, based on internal measurement, Y.P. Gunji et al
 the logical jump in shell changing in hermit crab and tool experiment in ants, M. Kitabayashi et al
 the neurobiology of semantics  how can machines be designed to have meanings, W.J. Freeman
 the emergence of contentful experience, M.H. Bickhard
 intentionality and foundations of logic  a new approach to neurocomputation, G. Basti.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Singapore ; River Edge, NJ : World Scientific, ©2001.
 Description
 Book — 1 online resource (xii, 309 pages) : illustrations
 Summary

 Consideration of emotion model and primitive language of robots, T. Ogata and S. Sugano
 an architecture for animallike behaviour selection, T. Kitamura
 a computation literary theory the ultimate products of the brain/mind machine, A. Tokosumi
 cooperation between neural networks within the brain, M. Dufosse et al
 brainlike functions in evolving connectionist systems for online, knowledgebased learning, N. Kasabov
 interrelationships, communication, semiotics and artificial consciousness, H.N.L. Teodorescu
 time emerges from incomplete clock, based on internal measurement, Y.P. Gunji et al
 the logical jump in shell changing in hermit crab and tool experiment in ants, M. Kitabayashi et al
 the neurobiology of semantics  how can machines be designed to have meanings, W.J. Freeman
 the emergence of contentful experience, M.H. Bickhard
 intentionality and foundations of logic  a new approach to neurocomputation, G. Basti.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Amsterdam ; Washington, DC : IOS Press ; Tokyo : Ohmsha, ©2002.
 Description
 Book — 1 online resource (x, 291 pages) : illustrations Digital: data file.
 Summary

 Cover; Title page; Preface; Acknowledgments; Contents; I. Data Collection; Toward Active Mining from Online Scientific Text Abstracts Using Preexisting Sources; Data Mining on the WAVEs
 WordofmouthAssisting Virtual Environments; Immune Networkbased Clustering for WWW Information Gathering/Visualization; Interactive Web Page Retrieval with Relational Learningbased Filtering Rules; Monitoring Partial Update of Web Pages by Interactive Relational Learning; Contextbased Classification of Technical Terms Using Support Vector Machines.
 Congress of Logic Applied to Technology (3rd : 2002 : São Paulo, Brazil)
 Amsterdam ; Washington, DC : IOS Press/Ohmsha, 2002.
 Description
 Book — 1 online resource (viii, 277 pages) : illustrations Digital: data file.
 Summary

 Cover; Title page; Contents; Retriever Prototype of a Case Based Reasoning: A Study Case; Dynamic Compaction Process of Metal Powder Media within Dies; Automated Theorem Proving for Manysorted Free Description Theory Based on Logic Translation; Annotated Logic and Negation as Failure; Multiagent System for Distribution System Operation; ArTbitrariness: Putting Computer Creativity to Work in Aesthetic Domains; An Overview of Fuzzy Numbers and Fuzzy Arithmetic; The Brain and Arithmetic Calculation; Evolving Arithmetical Knowledge in a Distributed Intelligent Processing System.
88. Advances in neural information processing systems 14 : proceedings of the 2001 conference [2002]
 Cambridge, Mass. : MIT Press, ©2002.
 Description
 Book — 1 online resource (2 volumes (1594 pages)) : illustrations
 Summary

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. The conference is interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, vision, speech and signal processing, reinforcement learning and control, implementations, and diverse applications. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented at the 2001 conference.
(source: Nielsen Book Data)
89. Blondie24 : playing at the edge of AI [2002]
 Fogel, David B.
 San Francisco : Morgan Kaufmann Publishers, ©2002.
 Description
 Book — 1 online resource (xvi, 404 pages) : illustrations
 Summary

 Part 1  Setting the Stage
 Chapter 1  Intelligent Machines: Imitating Life
 Chapter 2  Deep Blue: A Triumph of AI?
 Chapter 3  Building An Artificial Brain
 Chapter 4  Evolutionary Computation: Putting Nature to Work
 Chapter 5  Blue Hawaii: Natural Selection
 Chapter 6  Checkers
 Chapter 7  Chinook: The Manmachine Checkers Champion
 Chapter 8  Samuel's Learning Machine
 Chapter 9  The SamuelNewell Challenge
 Part 2  The Making of Blondie
 Chapter 10  Evolving in the Checkers Environment
 Chapter 11  In The Zone
 Chapter 12  A Repeat Performance
 Chapter 13  A New Dimension
 Chapter 14  Letting the Genie Out of the Bottle
 Chapter 15  Blondie24 Epilogue: The Future of Artificial Intelligence Appendix: Your Honor, I Object! Notes Index About the Author.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 IEEE International Workshop on Cellular Neural Networks and Their Applications (7th : 2002 : Frankfurt, Germany)
 River Edge, NJ : World Scientific, ©2002.
 Description
 Book — 1 online resource (xxvii, 671 pages) : illustrations (some color)
 Summary

 FOREWORD; CONTENTS; Keynote Address; The Origin of Complexity (presented, but paper not submitted); Plenary Session; The Role of Field Coupling in NanoScale Cellular Nonlinear Networks; Session Theory I; On the Relationship Between CNNs and PDEs; New SpatialTemporal Patterns and the First Programmable OnChip Bifurcation TestBed; On Stability of Full Range and Polynomial Type CNNs; A Study on Limit Cycles in Nearly Symmetric Cellular Neural Networks; An Improved Global Stability Result for Cellular Neural Networks with Time Delay; Session Applications I.
 SCCNNs for Chaotic Signals GenerationMoving Object Tracking on Panoramic Images; MPEG4 Based Modifications for an CNN Segmentation Chip; Watermarking for the Authentication of Video on CNNUM; An Analogic CNNAlgorithm of Pixel Level Snakes for Tracking and Surveillance Tasks; Session Theory II; On the Dynamics of a Class of Cellular Neural Networks; mLCNN: A CNN Model for ReactionDiffusion Processes in mComponent Systems; Emergence of Global Patterns in Connected Neural Networks; Influence of System NonUniformity on Dynamic Phenomena in Arrays of Coupled Nonlinear Networks.
 Boolean Design of Binary Initialized and Coupled CNN Image Processing OperatorsSession Physical Implementations I; ACE16K: A 128x128 Focal Plane Analog Processor with Digital I/O.; On the RTD Implementation of Simplicial Cellular Nonlinear Networks; Programmable Optical CNN Implementation Based on the Template Pixels' Angular Coding; Application Issues Of A Programmable Optical CNN Implementation; Configurable MultiLayer CNNUM Emulator on FPGA; Session Applications II (Poster); ObjectOriented Image Analysis via Analogic CNN Algorithms
 Part I: Motion Estimation.
 ObjectOriented Image Analysis via Analogic CNN Algorithms
 Part II: Image Synthesis and Consistency ObservationA CNN Path Planning for a Mobile Robot in an Environment with Obstacles; A CNN Based System to Blind Sources Separation of MEG Signals; DelayDriven Contrast Enhancement Using a Cellular Neural Network with StateDependant Delay; Plenary Session; Time as Coding Space for Information Processing in the Cerebral Cortex; Characterizing the SpatioTemporal Dynamics of the Epileptogenic Process with Nonlinear EEG Analyses; Session Bionics and Biologically Relevant Models I.
 Analyzing Multidimensional Neural Activity via CNNUMBasic Mammalian Retinal Effects on the Prototype Complex Cell CNN Universal Machine; Prediction of Epileptic Seizures by CNN with Linear Weight Functions; Biometric Authentication Based on Perceptual Resonance between CNN Emergent Patterns and Humans; CNN Based Central Pattern Generators with Sensory Feedback; Session Integrated Sensing and Processing; Mobile SensorActuator Networks: Opportunities and Challenges; Visual Feedback by Using a CNN Chip Prototype System; MultiTarget Tracking with Stored Program Adaptive CNN Universal Machines.
 International FLINS Conference (5th : 2002 : Ghent, Belgium)
 River Edge, N.J. : World Scientific, ©2002.
 Description
 Book — 1 online resource (xii, 591 pages) : illustrations
 Summary

 Invited lectures. Trends in computational intelligence in nuclear engineering / R.E. Uhrig
 Possibility theory in decision support systems / H. Prade
 Computing with wordssemantics / P.P. Wang
 pt. 1. Recent developments. Computing with words: the concept of conformity / M. Gemeinder
 Semantic additive and non additive measure as modal logic model of fuzzy sets and fuzzy measure / G. Resconi and I.B. Türksen
 A new latticevalued propositional logic (I): semantics / K. Qin and Y. Xu
 Fuzzy numerical methods / I. Perfilieva
 Solution of Dirichlet boundary value problem for the Poisson equation based on a fuzzy system / B.S. Moon [and others]
 A strong relevant logic approach to the calculus of fuzzy conditionals / J. Cheng and Y. Goto
 The [symbol]resolution field of indecomposable extremely simple form of latticevalued propositional logic LP(X) / W. Wang [and others]
 Fuzzy relation equations via basic predicate fuzzy logic / V. Novák, I. Perfilieva and S. Gottwald
 Underlying criteria in valued preference relations / J. Montero [and others]
 Model predictive control using fuzzy satisfactory optimization / S. Li and W. Qu
 Mirror strategy in game playing: combining fuzzy sets and genetic algorithm to improve strategies / A. Cincotti, V. Cutello and G. Sorace
 The extraction of linguistic knowledge using fuzzy logic and generalized quantifiers / A. Dvorák and V. Novák
 A speed improvement scheme in knowledge discovery of association rule algorithm for a market basket / W. Premchaiswadi [and others]
 Dynamic clustering based on maximum frequent itemsets for analysing purchase pattern / Y. Zhao and P. Shi
 Using soft computing techniques to integrate multiple kinds of attributes in data mining / S. Coppock and L. Mazlack
 Discovering association rules with degrees of support and implication (ARsi) / G. Chen [and others]
 The role of Occam's razor in activity based modeling / E. Moons [and others]
 Reliability demonstration of interiorouterset mode relevant in risk assessment / C. Huang
 Flexibility quantification in computer integrated manufacturing systems based on fuzzy cash flow analysis / A. Beskese, C. Kahraman and D. Ruan
 About the fusion of technicalspecification knowledge components / E. Grégoire
 Information diffusion method in risk analysis / H. Strang [and others]
 The theory of optimal information diffusion estimation and its application / X. Wang and Y. You
 Risk factor analysis and evaluation of natural disasters: application of the RIFAE framework to the 2000 TokaiFlood Disaster in Japan / G. Zhai [and others]
 Towards a soft representation of diversity in reliability theory / M. Oussalah and L. Strigini
 Analogy between multistate system and nonadditive reliability models / M. Oussalah and M. Newby.
 pt. 2. Computational intelligent systems. An architecture model of intelligent agents system to approach problems of distributed knowledge / F. Llorens, R. Rizo and M. Pujol
 Design of a timedelay feedback controller to chaotify continuoustime TakagiSugeno fuzzy systems / Z. Li and B. Zhang
 Online inference for fuzzy controllers in continuous domains / S. Lu
 Generalized predictive control with fuzzy constraints simulation / S. Li, G. Du and W. Qu
 Process identification through modular neural networks and rule extraction / B.J. van der Zwaag, K. Slump and L. Spaanenburg
 Automated image enhancement algorithm based on optimization of generalized fuzzy entropies (GFEs) / I.K. Vlachos and G.D. Sergiadis
 Integration of human knowledge and measured data for optimization of fabric hand / X. Zeng [and others]
 Fuzzy hidden Markov models for online training evaluation in virtual reality simulators / R.M. de Moraes and L. dos Santos Machado
 A new approach for plant monitoring using type2 fuzzy logic and fractal theory / O. Castillo and P. Melin
 Integration of fuzzy techniques and perception systems for ITS / R. Garcia [and others]
 Digital neural networks in the CAMbrain machine / H. Eeckhaut and J. Van Campenhout
 Hysteresis modelling using feedforward neural networks and its application to soft magnetic materials / D. Makaveev, L. Dupré and J. Melkebeek
 A new method for adaptive control of nonlinear plants using type2 fuzzy logic and neural networks / P. Melin and O. Castillo
 Analysis and modeling of field device tool interfaces / W. Zhang and C. Diedrich
 Comparing a genetic fuzzy and a neurofuzzy classifier for credit scoring / F. Hoffmann [and others]
 A modular neural network classifier for the recognition of occluded characters in automatic license plate reading / J.A.G. Nijhuis, A. Broersma and L. Spaanenburg
 Noise cleaning process using the fuzzy membership function / A. Thammano and P. Ruxpakawong
 A hybrid scheme, ART1 and feature matching, for Thai character recognition systems / N. Premchaiswadi [and others]
 Environmental systems modelling and diagnosis using a multiple model approach / K. Gasso, G. Mourot and J. Ragot
 Risk assessment of avalanches
 a fuzzy GIS application / M. Hemetsberger [and others]
 Land evaluation for surface irrigation using fuzzy representation and aggregation schemes / A. Tocatlidou [and others]
 Annoyance prediction with fuzzy rule bases / A. Verkeyn and D. Botteldooren.
 pt. 3. Applied research and nuclear applications. Realtime intelligent vision sensor for robot navigation using symmetry features / D. Popescu, K. Huebner and J. Zhang
 Selforganizing fuzzy system for visionbased position estimation / N. Popescu and J. Zhang
 Fuzzy adaptive robust tracking control for a class of uncertain nonlinear systems and its application / Y. Yang and C. Zhou
 Motion control of an hexapod walking machine using fuzzy state automata / D. Morano and L.M. Reyneri
 Equivalent linearization of 2way fuzzy adaptive system under nonparametric uncertainty and inconsistency / E. Gurkan [and others]
 Adaptive fuzzy neural control of nonlinear systems / Y. Gao, M.J. Er and C. Deng
 Toward perceptionbased robotics: a fuzzyarithmeticbased Lyapunov synthesis approach / C. Zhou, P.K. Yue and H.L. Sng
 Algorithmic lateral inhibition as a generic method for visual information processing with potential applications in robotics / A.E. Delgado and J. Mira
 A reinforcement learning method for dynamic obstacle avoidance in robotic mechanisms / D. Maravall and J. de Lope
 Intelligent navigation in partially unknown indoor environments / A. Poncela [and others]
 Evolutionary active force control of a 5link biped robot / L.C. Kwek [and others]
 Synthesis and evaluation analysis of the physical model indicator information by computing with words / J. Liu, D. Ruan and R. Carchon
 Fuzzylogic supported evaluation of the disposal costs and tariffs of highlevel radioactive waste / P.L. Kunsch, A. Fiordaliso and P. Fortemps
 Designing reduced scale thermalhydraulic experiments using genetic algorithms / C.M.F. Lapa, P.A.B. de Sampaio and C.M.N.A. Pereira
 Genetic based transient identification system design with automatic selection of meaningful variables / C.M.N.A. Pereira and R. Schirru
 Optimization of fuel reload in a BWR nuclear reactor using a recurrent neural network / J.J. Ortiz and I. Requena
 Neural network methods for radial profile reconstruction for ZEFF from bremsstrahlung data on the Textor tokamak / G. Verdoolaege, G. Telesca and G. Van Oost
 The use of non linear partial least square methods for online process monitoring as an alternative to artificial neural networks / P.F. Fantoni [and others]
 Improving feedwater crosscorrelation flow measurements in nuclear power plants with artifical neural networks / D. Roverso, D. Ruan and P.F. Fantoni
 Application of localized regularization methods for nuclear power plant sensor calibration monitoring / M.A. Buckner [and others].
(source: Nielsen Book Data)
92. Designing sociable robots [2002]
 Breazeal, Cynthia L.
 Cambridge, Mass. : MIT Press, ©2002.
 Description
 Book — 1 online resource (xviii, 263 pages) : illustrations
 Summary

 1. The vision of sociable robots
 2. Robot in society: a question of interface
 3. Insights from developmental psychology
 4. Designing sociable robots
 5. The physical robot
 6. The vision system
 7. The auditory system
 8. The motivation system
 9. The behavior system
 10. Facial animation and expression
 11. Expressive vocalization system
 12. Social constraints on animate vision
 13. Grand challenges of building sociable robots.
(source: Nielsen Book Data)
93. Intelligent technologiestheory and applications : new trends in intelligent technologies [2002]
 Amsterdam ; Washington, DC : IOS Press ; Tokyo : Ohmsha, 2002.
 Description
 Book — 1 online resource (xi, 346 pages) : illustrations. Digital: data file.
 Summary

Annotation Intelligent Technologies including neural network, evolutionary computations, fuzzy approach and mainly hybrid approaches are very promising tools to build intelligent technologies in general. The progress of each theory or application is provided by a number of various theoretical as well as applicational experiments. Machine intelligence is the only alternative how to increase the level of technology to make technology more humancentred and more effective for society. This book includes theoretical as well as applicational papers in the field of neural networks, fuzzy systems and mainly evolutionary computations which application potential was increased by enormous progress in computer power. Hybrid technologies are still progressing and are trying to make some more applications with their ability to learn and process fuzzy information. Neurogenetic systems are very interesting approach to make systems reconfigurable and online systems for realworld applications. The book is presenting papers from Japan, USA, Hungary, Poland, Germany, Finland, France, Slovakia, United Kingdom, Czech Republic and some other countries. This publication provides the latest state of the art in the field and could be contributed to theory and applications in the machine intelligence tools and their wide application potential in current and future technologies within the Information Society.
94. Knowledgebased intelligent information engineering systems and allied technologies : KES 2002 [2002]
 International Conference on KnowledgeBased Intelligent Information and Engineering Systems (2002 : University of Milan)
 Amsterdam ; Washington, DC : IOS Press/Ohmsha, ©2002.
 Description
 Book — 1 online resource (2 parts (1576 pages)) : illustrations Digital: data file.
 Herbrich, Ralf.
 Cambridge, Mass. : MIT Press, ©2002.
 Description
 Book — 1 online resource (xx, 364 pages) : illustrations.
 Summary

An overview of the theory and application of kernel classification methods. Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifiera limited, but wellestablished and comprehensively studied modeland extends its applicability to a wide range of nonlinear patternrecognition tasks such as natural language processing, machine vision, and biological sequence analysis. This book provides the first comprehensive overview of both the theory and algorithms of kernel classifiers, including the most recent developments. It begins by describing the major algorithmic advances: kernel perceptron learning, kernel Fisher discriminants, support vector machines, relevance vector machines, Gaussian processes, and Bayes point machines. Then follows a detailed introduction to learning theory, including VC and PACBayesian theory, datadependent structural risk minimization, and compression bounds. Throughout, the book emphasizes the interaction between theory and algorithms: how learning algorithms work and why. The book includes many examples, complete pseudo code of the algorithms presented, and an extensive source code library.
(source: Nielsen Book Data)
 Herbrich, Ralf.
 Cambridge, Mass. : MIT Press, ©2002.
 Description
 Book — 1 online resource (xx, 364 pages) : illustrations.
 Summary

An overview of the theory and application of kernel classification methods. Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifiera limited, but wellestablished and comprehensively studied modeland extends its applicability to a wide range of nonlinear patternrecognition tasks such as natural language processing, machine vision, and biological sequence analysis. This book provides the first comprehensive overview of both the theory and algorithms of kernel classifiers, including the most recent developments. It begins by describing the major algorithmic advances: kernel perceptron learning, kernel Fisher discriminants, support vector machines, relevance vector machines, Gaussian processes, and Bayes point machines. Then follows a detailed introduction to learning theory, including VC and PACBayesian theory, datadependent structural risk minimization, and compression bounds. Throughout, the book emphasizes the interaction between theory and algorithms: how learning algorithms work and why. The book includes many examples, complete pseudo code of the algorithms presented, and an extensive source code library.
(source: Nielsen Book Data)
 Herbrich, Ralf.
 Cambridge, Mass. : MIT Press, ©2002.
 Description
 Book — 1 online resource (xx, 364 pages) : illustrations
 Summary

An overview of the theory and application of kernel classification methods. Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifiera limited, but wellestablished and comprehensively studied modeland extends its applicability to a wide range of nonlinear patternrecognition tasks such as natural language processing, machine vision, and biological sequence analysis. This book provides the first comprehensive overview of both the theory and algorithms of kernel classifiers, including the most recent developments. It begins by describing the major algorithmic advances: kernel perceptron learning, kernel Fisher discriminants, support vector machines, relevance vector machines, Gaussian processes, and Bayes point machines. Then follows a detailed introduction to learning theory, including VC and PACBayesian theory, datadependent structural risk minimization, and compression bounds. Throughout, the book emphasizes the interaction between theory and algorithms: how learning algorithms work and why. The book includes many examples, complete pseudo code of the algorithms presented, and an extensive source code library.
(source: Nielsen Book Data)
98. Learning with kernels : support vector machines, regularization, optimization, and beyond [2002]
 Schölkopf, Bernhard.
 Cambridge, Mass. : MIT Press, ©2002.
 Description
 Book — 1 online resource (xviii, 626 pages) : illustrations
 Summary

 Series Foreword; Preface; 1
 A Tutorial Introduction; I
 Concepts and Tools; 2
 Kernels; 3
 Risk and Loss Functions; 4
 Regularization; 5
 Elements of Statistical Learning Theory; 6
 Optimization; II
 Support Vector Machines; 7
 Pattern Recognition; 8
 SingleClass Problems: Quantile Estimation and Novelty Detection; 9
 Regression Estimation; 10
 Implementation; 11
 Incorporating Invariances; 12
 Learning Theory Revisited; III
 Kernel Methods; 13
 Designing Kernels; 14
 Kernel Feature Extraction; 15
 Kernel Fisher Discriminant; 16
 Bayesian Kernel Methods.
 17
 Regularized Principal Manifolds18
 PreImages and Reduced Set Methods; A
 Addenda; B
 Mathematical Prerequisites; References; Index; Notation and Symbols.
(source: Nielsen Book Data)
99. Least squares support vector machines [2002]
 River Edge, NJ : World Scientific, 2002.
 Description
 Book — 1 online resource (xiv, 294 pages) : illustrations
 Summary

Annotation. This book focuses on Least Squares Support Vector Machines (LSSVMs) which are reformulations to standard SVMs. LSSVMs are closely related to regularization networks and Gaussian processes but additionally emphasize and exploit primaldual interpretations from optimization theory. The authors explain the natural links between LSSVM classifiers and kernel Fisher discriminant analysis. Bayesian inference of LSSVM models is discussed, together with methods for imposing spareness and employing robust statistics. The framework is further extended towards unsupervised learning by considering PCA analysis and its kernel version as a oneclass modelling problem. This leads to new primaldual support vector machine formulations for kernel PCA and kernel CCA analysis. Furthermore, LSSVM formulations are given for recurrent networks and control. In general, support vector machines may pose heavy computational challenges for large data sets. For this purpose, a method of fixed size LSSVM is proposed where the estimation is done in the primal space in relation to a Nystrom sampling with active selection of support vectors. The methods are illustrated with several examples.
100. .Net mobile web developer's guide [2002]
 Milroy, Steve.
 Rockland, Massachusetts : Syngress Pub., ©2002.
 Description
 Book — 1 online resource (xxiv, 407 pages) : illustrations
 Summary

Introducing Microsoft's flagship wireless development tool The .NET Mobile Web Developer's Guide will provide readers with a solid guide to developing mobile applications using Microsoft technologies. The focus of this book is on using ASP.NET and the .NET mobile SDK. It provides an introduction to the .NET platform and goes into moderate details on ASP.NET to allow readers to start developing ASP.NET applications. In addition, this book will give the readers the insight to use the various Microsoft technologies for developing mobile applications. This book assumes the readers have experience in developing web applications and are familiar with any one of the serverside technologies like ASP, JSP or PHP.
(source: Nielsen Book Data)
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