1  20
Next
 German Conference on Artificial Intelligence (23rd : 1999 : Bonn, Germany)
 Berlin ; New York : Springer, ©1999.
 Description
 Book — 1 online resource (xi, 310 pages) : illustrations Digital: text file; PDF.
 Summary

 Invited Papers
 From AI to Systemic Knowledge Management
 MINERVA: A TourGuide Robot that Learns
 Dynamics, Morphology, and Materials in the Emergence of Cognition
 Natural Language Description of Image Sequences as a Form of Knowledge Representation
 Knowledge Discovery in Spatial Databases
 Cooperative Distributed Vision: Dynamic Integration of Visual Perception, Action, and Communication
 Technical PapersSection 1
 Computing Probabilistic Least Common Subsumers in Description Logics
 Revising Nonmonotonic Theories: The Case of Defeasible Logic
 On the Translation of Qualitative Spatial Reasoning Problems into Modal Logics
 Following Conditional Structures of Knowledge
 Section 2
 A Theory of FirstOrder Counterfactual Reasoning
 Logic
 Based Choice of Projective Terms
 Knowledge Based Automatic Composition and Variation of Melodies for Minuets in Early Classical Style
 Inferring Flow of Control in Program Synthesis by Example
 Section 3
 Compilation Schemes: A Theoretical Tool for Assessing the Expressive Power of Planning Formalisms
 Generalized Cases: Representation and Steps Towards Efficient Similarity Assessment
 Be Busy and Unique
 or Be History
 The Utility Criterion for Removing Units in SelfOrganizing Networks
 Section 4
 Development of Decision Support Algorithms for Intensive Care Medicine: A New Approach Combining Time Series Analysis and a Knowledge Base System with Learning and Revision Capabilities
 Object Recognition with Shape Prototypes in a 3D Construction Scenario
 Probabilistic, PredictionBased Schedule Debugging for Autonomous Robot Office Couriers
 Section 5
 Collaborative Multirobot Localization
 Object Classification Using Simple, Colour Based Visual Attention and a Hierarchical Neural Network for Neurosymbolic Integration
 A Flexible Architecture for Driver Assistance Systems
 Short Papers
 A Theory for Causal Reasoning
 Systematic vs. Local Search for SAT
 Information Environments for Software Agents
 Improving Reasoning Efficiency for Subclasses of Allen's Algebra with Instantiation Intervals
 Agents in Traffic Modelling
 From Reactive to Social Behaviour
 TimeEffect Relations of Medical Interventions in a Clinical Information System.
 Portuguese Conference on Artificial Intelligence (8th : 1997 : Coimbra, Portugal)
 Berlin ; New York : Springer, ©1997.
 Description
 Book — 1 online resource (xiv, 388 pages) : illustrations
 Summary

 Flexible proofreplay with heuristics
 Flexible reenactment of proofs
 Inference rights for controlling search in generating theorem provers
 A retrieval method for exploration of a case memory
 Incremental concept evolution based on adaptive feature weighting
 A 01 quadratic knapsack problem for modelizing and solving the constraint satisfaction problems
 An algorithm for solving systems of linear diophantine equations in naturals
 GenSAT: A navigational approach
 Timetabling using demand profiles
 Intelligent VR training
 Training strategies and knowledge acquisition: Using the same reflective tools for different purposes
 About the intended meaning of a linguistic negation
 Integration of inheritance in SNePS
 Measures of uncertainty and independence concept in different calculi
 A Multiagent approach to firstorder logic
 Modelling dynamic aspects of intentions
 Multiagent negotiation algorithms for resources cost estimation: A case study
 Parla: A cooperation language for cognitive multiagent systems
 Vivid agents arguing about distributed extended logic programs
 Approximate reasoning
 New results about subadmissibility for general families of heuristic search algorithms
 Fixed point classification method for qualitative simulation
 Contextual logic of change and the ramification problem
 Temporal reasoning about actor programs
 A CLP model to the job sequencing problem
 A new approach for extracting rules from a trained neural network
 Bayesian networks, rule induction and logistic regression in the prediction of women survival suffering from breast cancer
 Controlling for unexpected goals when planning in a mixedinitiative setting
 Cooperative memory structures and commonsense knowledge for planning
 Diagonalization and type rewriting in clam
 Granularity for explanation
 Object model of intelligent tutoring shell
 Resource allocation on agent metasocieties
 Diagnostic information at your fingertips!
 Reasoning about actions with abductive logic programming
 Dimensions of embodiments: Possible futures for cognitive science (Abstract)
 Machine learning meets natural language (Abstract).
3. Intelligence : new visions of AI in practice [1999  2001]
 Intelligence (New York, N.Y. : 1999)
 New York, NY : Association for Computing Machinery, c1999c2001.
 Description
 Journal/Periodical — 3 v. : ill. ; 28 cm.
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Q335 .A8 V.10 1999  Available 
 1st MIT Press ed.  Cambridge, Mass. : MIT Press, 1994.
 Description
 Book — 1 online resource (viii, 462 pages) : illustrations.
 Summary

This major collection of short essays reviews the scope and progress of research in artificial intelligence over the past two decades. Seminal and mostcited papers from the journal Artificial Intelligence are revisited by the authors who describe how their research has been developed, both by themselves and by others, since the journals first publication.The twentyeight papers span a wide variety of domains, including truth maintainance systems and qualitative process theory, chemical structure analysis, diagnosis of faulty circuits, and understanding visual scenes; they also span a broad range of methodologies, from AI's mathematical foundations to systems architecture.The volume is dedicated to Allen Newell and concludes with a section of fourteen essays devoted to a retrospective on the strength and vision of his work.Sections/Contributors: Artificial Intelligence in Perspective, D. G. Bobrow. Foundations. J. McCarthy, R. C. Moore, A. Newell, N. J. Nilsson, J. Gordon and E. H. Shortliffe, J. Pearl, A. K. Mackworth and E. C. Freuder, J. de Kleer. Vision. H. G. Barrow and J. M. Tenenbaum, B. K. P. Horn and B. Schunck, K. Ikeuchi, T. Kanade. Qualitative Reasoning. J. de Kleer, K. D. Forbus, B. J. Kuipers, Y. Iwasake and H. A Simon. Diagnosis. R. Davis, M. R. Genesereth, P. Szolovits and S. G. Pauker, R. Davis, B. G. Buchanan and E. H. Shortliffe, W. J. Clancey. Architectures. J. S. Aikins, B. HayesRoth, M. J. Stefik et al. Systems. R. E. Fikes and N. J. Nilsson, E. A Feigenbaum and B. G. Buchanan, J. McDermott. Allen Newell. H. A. Simon, M. J. Stefik and S. W. Smoliar, M. A. Arbib, D. C. Dennett, Purves, R. C. Schank and M. Y. Jona, P. S. Rosenbloom and J. E. Laird, P. E. Agre.
(source: Nielsen Book Data)
 1st MIT Press ed.  Cambridge, Mass. : MIT Press, 1994.
 Description
 Book — 1 online resource (viii, 462 pages) : illustrations.
 Summary

This major collection of short essays reviews the scope and progress of research in artificial intelligence over the past two decades. Seminal and mostcited papers from the journal Artificial Intelligence are revisited by the authors who describe how their research has been developed, both by themselves and by others, since the journals first publication.The twentyeight papers span a wide variety of domains, including truth maintainance systems and qualitative process theory, chemical structure analysis, diagnosis of faulty circuits, and understanding visual scenes; they also span a broad range of methodologies, from AI's mathematical foundations to systems architecture.The volume is dedicated to Allen Newell and concludes with a section of fourteen essays devoted to a retrospective on the strength and vision of his work.Sections/Contributors: Artificial Intelligence in Perspective, D. G. Bobrow. Foundations. J. McCarthy, R. C. Moore, A. Newell, N. J. Nilsson, J. Gordon and E. H. Shortliffe, J. Pearl, A. K. Mackworth and E. C. Freuder, J. de Kleer. Vision. H. G. Barrow and J. M. Tenenbaum, B. K. P. Horn and B. Schunck, K. Ikeuchi, T. Kanade. Qualitative Reasoning. J. de Kleer, K. D. Forbus, B. J. Kuipers, Y. Iwasake and H. A Simon. Diagnosis. R. Davis, M. R. Genesereth, P. Szolovits and S. G. Pauker, R. Davis, B. G. Buchanan and E. H. Shortliffe, W. J. Clancey. Architectures. J. S. Aikins, B. HayesRoth, M. J. Stefik et al. Systems. R. E. Fikes and N. J. Nilsson, E. A Feigenbaum and B. G. Buchanan, J. McDermott. Allen Newell. H. A. Simon, M. J. Stefik and S. W. Smoliar, M. A. Arbib, D. C. Dennett, Purves, R. C. Schank and M. Y. Jona, P. S. Rosenbloom and J. E. Laird, P. E. Agre.
(source: Nielsen Book Data)
 1st MIT Press ed.  Cambridge, Mass. : MIT Press, 1996.
 Description
 Book — 1 online resource (vi, 767 pages) : illustrations.
 Summary

 Computational research on interaction and agency / P.E. Agre
 Sensorimotor transformations in the worlds of frogs and robots / M.A. Arbib and J.S. Liaw
 Learning to act using realtime dynamic programming / A.G. Barto, S.J. Bradtke, and S.P. Singh
 Learning dynamics: systems identification for perceptually challenged agents / K. Basye, T. Dean, and L.P. Kaelbling
 Dynamical systems perspective on agentenvironment interaction / R.D. Beer
 On information invariants in robotics / B.R. Donald
 Stabilization of environments / K.J. Hammond, T.M. Converse, and J.W. Grass
 Architecture for adaptive intelligent systems / B. HayesRoth
 Analysis of adaptation and environment / I. Horswill
 Intelligent use of space / D. Kirsh
 Indexical knowledge and robot actiona logical account / Y. Lespérance and H.J. Levesque
 Exploiting patterns of interaction to achieve reactive behavior / D.M. Lyons and A.J. Hendriks
 Situated view of representation and control / S.J. Rosenschein and L.P. Kaelbling
 Use of dynamics in an intelligent controller for a space faring rescue robot / M. Schoppers
 On social laws for artificial agent societies: offline design / Y. Shohaam and M. Tennenholtz
 Instructions, intentions, and expectations / B. Webber [and others]
 Reinforcement learning of nonmarkov decision processes / S.D. Whitehead and L.J. Lin.
(source: Nielsen Book Data)
 1st MIT Press ed.  Cambridge, Mass. : MIT Press, 1996.
 Description
 Book — 1 online resource (vi, 767 pages) : illustrations.
 Summary

 Computational research on interaction and agency / P.E. Agre
 Sensorimotor transformations in the worlds of frogs and robots / M.A. Arbib and J.S. Liaw
 Learning to act using realtime dynamic programming / A.G. Barto, S.J. Bradtke, and S.P. Singh
 Learning dynamics: systems identification for perceptually challenged agents / K. Basye, T. Dean, and L.P. Kaelbling
 Dynamical systems perspective on agentenvironment interaction / R.D. Beer
 On information invariants in robotics / B.R. Donald
 Stabilization of environments / K.J. Hammond, T.M. Converse, and J.W. Grass
 Architecture for adaptive intelligent systems / B. HayesRoth
 Analysis of adaptation and environment / I. Horswill
 Intelligent use of space / D. Kirsh
 Indexical knowledge and robot actiona logical account / Y. Lespérance and H.J. Levesque
 Exploiting patterns of interaction to achieve reactive behavior / D.M. Lyons and A.J. Hendriks
 Situated view of representation and control / S.J. Rosenschein and L.P. Kaelbling
 Use of dynamics in an intelligent controller for a space faring rescue robot / M. Schoppers
 On social laws for artificial agent societies: offline design / Y. Shohaam and M. Tennenholtz
 Instructions, intentions, and expectations / B. Webber [and others]
 Reinforcement learning of nonmarkov decision processes / S.D. Whitehead and L.J. Lin.
(source: Nielsen Book Data)
8. PC AI. [1987  2001]
 [Phoenix, Ariz.] : Knowledge Technology, c1987c2001.
 Description
 Journal/Periodical — 15 v. : ill. ; 28 cm.
 Online
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Q334 .P32 V.7:NO.2V.11:NO.3  Available 
Q334 .P32 V.4:NO.5V.6:NO.6  Available 
Q334 .P32 V.3:NO.1V.4:NO.4  Available 
Q334 .P32 V.1:NO.1V.2:NO.4  Available 
 ILP99 (1999 : Bled, Slovenia)
 Berlin ; New York : Springer, ©1999.
 Description
 Book — 1 online resource (viii, 302 pages) : illustrations
 Summary

 I Invited Papers. Probabilistic Relational Models. Inductive Databases. Some Elements of Machine Learning. II Contributed Papers. Refinement Operators Can Be (Weakly) Perfect. Combining DivideandConquer and SeparateandConquer for Efficient and Effective Rule Induction. Refining Complete Hypotheses in ILP. Acquiring Graphic Design Knowledge with Nonmonotonic Inductive Learning. Morphosyntactic Tagging of Slovene Using Progol. Experiments in Predicting Biodegradability. 1BC: A FirstOrder Bayesian Classifier. Sorted Downward Refinement: Building Background Knowledge into a Refinement Operator for Inductive Logic Programming. A Strong Complete Schema for Inductive Functional Logic Programming. Application of Different Learning Methods to Hungarian PartofSpeech Tagging. Combining LAPIS and WordNet for the Learning of LR Parsers with Optimal Semantic Constraints. Learning Word Segmentation Rules for Tag Prediction. Approximate ILP Rules by Backpropagation Neural Network: A Result on Thai Character Recognition. Rule Evaluation Measures: A Unifying View. Improving Part of Speech Disambiguation Rules by Adding Linguistic Knowledge. On Sufficient Conditions for Learnability of Logic Programs from Positive Data. A Bounded Search Space of Clausal Theories. Discovering New Knowledge from Graph Data Using Inductive Logic Programming. Analogical Prediction. Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms. Theory Recovery. Instance based function learning. Some Properties of Inverse Resolution in Normal Logic Programs. An Assessment of ILPassisted models for toxicology and the PTE3 experiment.
 (source: Nielsen Book Data)
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 ILP98 (8th : 1998 : Madison, Wis.)
 Berlin ; New York : Springer, 1998.
 Description
 Book — 1 online resource (viii, 299 pages)
 Summary

 Attributevalue learning versus inductive logic programming: The missing links
 Advances in ILP theory and implementations
 Application of ILP to problems in chemistry and biology
 Relational reinforcement learning
 Learning firstorder acyclic Horn programs from entailment
 Combining statistical and relational methods for learning in hypertext domains
 Application of inductive logic programming to discover rules governing the threedimensional topology of protein structure
 Term comparisons in firstorder similarity measures
 Stochastic propositionalization of nondeterminate background knowledge
 A stochastic simple similarity
 Using prior probabilities and density estimation for relational classification
 Induction of Constraint Grammarrules using Progol
 A hybrid approach to word segmentation
 Learning multilingual morphology with Clog
 Using ILPsystems for verification and validation of multiagent systems
 Inducing shogi heuristics using inductive logic programming
 Repeat learning using predicate invention
 Normal programs and multiple predicate learning
 Strongly typed inductive concept learning
 Functionfree Horn clauses are hard to approximate
 DOGMA: A GAbased relational learner
 Generalization under implication by ?subsumption
 Prolog, refinements and RLGG's
 Learning structurally indeterminate clauses
 Completing Inverse Entailment
 Distances and limits on Herbrand interpretations
 Relational distancebased clustering
 A framework for defining distances between firstorder logic objects
 Detecting traffic problems with ILP
 A comparison of ILP and propositional systems on propositional traffic data.
 German Conference on Artificial Intelligence (16th : 1992 : Bonn, Germany)
 Berlin ; New York : Springer, ©1993.
 Description
 Book — 1 online resource (xi, 397 pages) : illustrations
 Summary

 How to construct a logic for your application. A model elimination calculus with builtin theories. A new sorted logic. An explanatory framework for human theorem proving. Towards firstorder deduction based on Shannon graphs. Success and failure of expert systems in. different fields of industrial application. Viewing knowledge engineering as a symbiosis of Modeling to make sense and modeling to implement systems. Cases as a basis for knowledge acquisition in the preformal phases of knowledge engineering. Controlling generate & test in any time. Efficient computation of solutions for contradictory time interval networks. Extensions of concept languages for a mechanical engineering application. Combining terminological and rulebased reasoning for abstraction processes. Forward logic evaluation: Compiling a partially evaluated metainterpreter into the WAM. Concept support as a method for programming neural networks with symbolic knowledge. A heuristic inductive generalization method and its application to VLSIdesign. Learning plan abstractions. On discontinuous QFunctions in reinforcement learning. An intelligent tutoring system for classification problem solving. Knowledgebased processing of medical language: A language engineering approach. Text planning in ITEX: A hybrid approach. Yes/no questions with negation: Towards integrating semantics and pragmatics. An efficient decision algorithm for feature logic. Universally quantified queries in languages with ordersorted logics. A semantic view of explanation. Goaldriven similarity assessment. Delegated negotiation for resource reallocation. Towards a specification language for cooperation methods. Improving operating system usage. The role of user models for conflicts in a constraintbased model of generation. Criteria in natural language generation: Minimal criteria and their impacts. Terminological representation, natural language & relation algebra. Linking humans and intelligent systems or: What are user agents good for?. An advisor for the management of the acute radiation syndrome.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Society for the Study of Artificial Intelligence and Simulation of Behaviour. Conference (9th : 1993 : University of Birmingham)
 Amsterdam ; Washington, DC : IOS Press, 1993.
 Description
 Book — viii, 291 p. : ill. ; 24 cm.
 Summary

Dealing with the theme of "prospects for artificial inteligence as the general science of intelligence", this work covers a wide range of topics. It attempts to identify trends and projects into the future, instead of simply surveying past achievements. The editor first introduces attempts to define the designbased approach to the study of intelligence, that characterizes IA. Following this, contributing papers report on work already done. Thus the subjects discussed include natural language, evolutionary AI, robotics, game playing, tutoring systems, cognitive modelling, SOAR, neural nets, and the modelling of motivation and emotions.
(source: Nielsen Book Data)
 Online
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Q334 .S6315 1993  Available 
 Berlin ; New York : SpringerVerlag, ©1986.
 Description
 Book — 1 online resource (v, 313 pages) : illustrations
 Summary

 Knowledge representation: Features of knowledge
 Deduction and computation
 An introduction to automated deduction
 Fundamental mechanisms in machine learning and inductive inference
 Methods of automated reasoning
 Term rewriting as a basis for the design of a functional and parallel programming language
 Concurrent Prolog: A progress report.
 Canadian Society for Computational Studies of Intelligence. Conference (12th : 1998 : Vancouver, B.C.)
 Berlin ; New York : Springer, ©1998.
 Description
 Book — 1 online resource (xii, 466 pages) : illustrations
 Summary

 Sokoban: Evaluating standard singleagent search techniques in the presence of deadlock
 A heuristic incremental modeling approach to course timetabling
 Planning strategy representation in DoLittle
 Establishing logical connectivity between query keywords and database contents
 Testdriving tanka: Evaluating a semiautomatic system of text analysis for knowledge acquisition
 An object indexing methodology as support to object recognition
 Oracles and assistants: Machine learning applied to network supervision
 A common multiagent testbed for diverse seamless personal information networking applications
 A hybrid genetic algorithm for the vehicle routing problem with time windows
 Maintaining genetic diversity in genetic algorithms through coevolution
 The effect of genetic operator probabilities and selection strategies on the performance of a genetic algorithm
 The impact of external dependency in genetic programming primitives
 Quality control in the concept learning process
 Grapheme generation in learning to read english words
 A trainable bracketer for noun modifiers
 Lessons learned in the development and implementation of a bilingual nationally accessible knowledgebased system
 Selecting the next action with constraints
 Poker as a testbed for AI research
 Fault prediction in the telephone access loop using a neural network
 Learning english syllabification rules
 Characterizing tractable CSPs
 An attribute redundancy measure for clustering
 On the complexity of VLSIfriendly neural networks for classification problems
 String clustering and statistical validation of clusters
 Finding partitions for learning control of dynamic systems
 A relational modeling of cognitive maps
 Distance constraint arrays: A model for reasoning on intervals with qualitative and quantitative distances
 Revising TimegraphII
 Temporally invariant junction tree for inference in dynamic bayesian network
 Utility theorybased user models for intelligent interface agents
 A hybrid convergent method for learning probabilistic networks
 Relational concepts and the fourier transform: An empirical study
 ELEM2: A learning system for more accurate classifications
 Sequential instancebased learning
 Predicate invention from a few examples.
 ILP (Conference) (6th : 1996 : Stockholm, Sweden)
 Berlin ; New York : Springer, ©1997.
 Description
 Book — 1 online resource (viii, 396 pages) : illustrations
 Summary

 Inductive logic programming for natural language processing. An initial experiment into stereochemistrybased drug design using inductive logic programming. Applying ILP to diterpene structure elucidation from 13C NMR spectra. Analysis and prediction of piano performances using inductive logic programming. Noise detection and elimination applied to noise handling in a KRK chess endgame. Feature construction with inductive logic programming: A study of quantitative predictions of biological activity by structural attributes. Polynomialtime learning in logic programming and constraint logic programming. Analyzing and learning ECG waveforms. Learning rules that classify ocular fundus images for glaucoma diagnosis. A new design and implementation of progol by bottomup computation. Inductive logic program synthesis with DIALOGS. Relational knowledge discovery in databases. Efficient ?subsumption based on graph algorithms. Integrity constraints in ILP using a Monte Carlo approach. Restructuring chain datalog programs. Topdown induction of logic programs from incomplete samples. Least generalizations under implication. Efficient proof encoding. Learning Logic programs with random classification noise. Handling Quantifiers in ILP. Learning from positive data. ?Subsumption and its application to learning from positiveonly examples.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 ILP (Conference) (7th : 1997 : Prague, Czech Republic)
 Berlin ; New York : Springer, ©1997.
 Description
 Book — 1 online resource (viii, 308 pages) : illustrations Digital: text file.PDF.
 Summary

 Knowledge discovery in databases: An overview. On the complexity of some Inductive Logic Programming problems. Inductive logic programming and constraint logic programming (abstract). Learning phonetic rules in a speech recognition system. Cautious induction in inductive logic programming. Generating numerical literals during refinement. Lookahead and discretization in ILP. Data mining via ILP: The application of Progol to a database of enantioseparations. Partofspeech tagging using Progol. Maximum Entropy modeling with Clausal Constraints. Mining association rules in multiple relations. Using logical decision trees for clustering. Induction of Slovene nominal paradigms. Normal forms for inductive logic programming. On a sufficient condition for the existence of most specific hypothesis in progol. Induction of logic programs with more than one recursive clause by analyzing saturations. A logical framework for graph theoretical decision tree learning. Learning with abduction. Systematic Predicate Invention in Inductive Logic Programming. Learning programs in the event calculus. Distance between Herbrand interpretations: A measure for approximations to a target concept. Realizing Progol by forward reasoning. Probabilistic firstorder classification. Learning Horn definitions with equivalence and membership queries. Using abstraction schemata in inductive logic programming. Distance induction in first order logic. Carcinogenesis predictions using ILP. Discovery of firstorder regularities in a relational database using ofine candidate determination. Which hypotheses can be found with inverse entailment?.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Poole, David L. (David Lynton), 1958 author. Author
 Second edition.  Cambridge, United Kingdom : Cambridge University Press, 2017.
 Description
 Book — xxviii, 792 pages : illustrations ; 27 cm
 Summary

 Machine generated contents note:
 I. Agents in the World: What are Agents and How Can They be Built?
 1. Artificial Intelligence and Agents
 1.1. What is Artificial Intelligence?
 1.1.1. Artificial and Natural Intelligence
 1.2. A Brief History of Artificial Intelligence
 1.2.1. Relationship to Other Disciplines
 1.3. Agents Situated in Environments
 1.4. Designing Agents
 1.4.1. Design Time, Offline and Online Computation
 1.4.2. Tasks
 1.4.3. Defining a Solution
 1.4.4. Representations
 1.5. Agent Design Space
 1.5.1. Modularity
 1.5.2. Planning Horizon
 1.5.3. Representation
 1.5.4. Computational Limits
 1.5.5. Learning
 1.5.6. Uncertainty
 1.5.7. Preference
 1.5.8. Number of Agents
 1.5.9. Interaction
 1.5.10. Interaction of the Dimensions
 1.6. Prototypical Applications
 1.6.1. An Autonomous Delivery Robot
 1.6.2. A Diagnostic Assistant
 1.6.3. An Intelligent Tutoring System
 1.6.4. A Trading Agent
 1.6.5. Smart House
 1.7. Overview of the Book
 1.8. Review
 1.9. References and Further Reading
 1.10. Exercises
 2. Agent Architectures and Hierarchical Control
 2.1. Agents
 2.2. Agent Systems
 2.2.1. The Agent Function
 2.3. Hierarchical Control
 2.4. Acting with Reasoning
 2.4.1. Agents Modeling the World
 2.4.2. Knowledge and Acting
 2.4.3. Design Time and Offline Computation
 2.4.4. Online Computation
 2.5. Review
 2.6. References and Further Reading
 2.7. Exercises
 II. Reasoning, Planning and Learning with Certainty
 3. Searching for Solutions
 3.1. Problem Solving as Search
 3.2. State Spaces
 3.3. Graph Searching
 3.3.1. Formalizing Graph Searching
 3.4. A Generic Searching Algorithm
 3.5. Uninformed Search Strategies
 3.5.1. BreadthFirst Search
 3.5.2. DepthFirst Search
 3.5.3. Iterative Deepening
 3.5.4. LowestCostFirst Search
 3.6. Heuristic Search
 3.6.1. A* Search
 3.6.2. Designing a Heuristic Function
 3.7. Pruning the Search Space
 3.7.1. Cycle Pruning
 3.7.2. MultiplePath Pruning
 3.7.3. Summary of Search Strategies
 3.8. More Sophisticated Search
 3.8.1. Branch and Bound
 3.8.2. Direction of Search
 3.8.3. Dynamic Programming
 3.9. Review
 3.10. References and Further Reading
 3.11. Exercises
 4. Reasoning with Constraints
 4.1. Possible Worlds, Variables, and Constraints
 4.1.1. Variables and Worlds
 4.1.2. Constraints
 4.1.3. Constraint Satisfaction Problems
 4.2. GenerateandTest Algorithms
 4.3. Solving CSPs Using Search
 4.4. Consistency Algorithms
 4.5. Domain Splitting
 4.6. Variable Elimination
 4.7. Local Search
 4.7.1. Iterative Best Improvement
 4.7.2. Randomized Algorithms
 4.7.3. Local Search Variants
 4.7.4. Evaluating Randomized Algorithms
 4.7.5. Random Restart
 4.8. PopulationBased Methods
 4.9. Optimization
 4.9.1. Systematic Methods for Optimization
 4.9.2. Local Search for Optimization
 4.10. Review
 4.11. References and Further Reading
 4.12. Exercises
 5. Propositions and Inference
 5.1. Propositions
 5.1.1. Syntax of Propositional Calculus
 5.1.2. Semantics of the Propositional Calculus
 5.2. Propositional Constraints
 5.2.1. Clausal Form for Consistency Algorithms
 5.2.2. Exploiting Propositional Structure in Local Search
 5.3. Propositional Definite Clauses
 5.3.1. Questions and Answers
 5.3.2. Proofs
 5.4. Knowledge Representation Issues
 5.4.1. Background Knowledge and Observations
 5.4.2. Querying the User
 5.4.3. KnowledgeLevel Explanation
 5.4.4. KnowledgeLevel Debugging
 5.5. Proving by Contradiction
 5.5.1. Horn Clauses
 5.5.2. Assumables and Conflicts
 5.5.3. ConsistencyBased Diagnosis
 5.5.4. Reasoning with Assumptions and Horn Clauses
 5.6. Complete Knowledge Assumption
 5.6.1. Nonmonotonic Reasoning
 5.6.2. Proof Procedures for Negation as Failure
 5.7. Abduction
 5.8. Causal Models
 5.9. Review
 5.10. References and Further Reading
 5.11. Exercises
 6. Planning with Certainty
 6.1. Representing States, Actions, and Goals
 6.1.1. Explicit StateSpace Representation
 6.1.2. The STRIPS Representation
 6.1.3. FeatureBased Representation of Actions
 6.1.4. Initial States and Goals
 6.2. Forward Planning
 6.3. Regression Planning
 6.4. Planning as a CSP
 6.4.1. Action Features
 6.5. PartialOrder Planning
 6.6. Review
 6.7. References and Further Reading
 6.8. Exercises
 7. Supervised Machine Learning
 7.1. Learning Issues
 7.2. Supervised Learning
 7.2.1. Evaluating Predictions
 7.2.2. Types of Errors
 7.2.3. Point Estimates with No Input Features
 7.3. Basic Models for Supervised Learning
 7.3.1. Learning Decision Trees
 7.3.2. Linear Regression and Classification
 7.4. Overfitting
 7.4.1. Pseudocounts
 7.4.2. Regularization
 7.4.3. Cross Validation
 7.5. Neural Networks and Deep Learning
 7.6. Composite Models
 7.6.1. Random Forests
 7.6.2. Ensemble Learning
 7.7. CaseBased Reasoning
 7.8. Learning as Refining the Hypothesis Space
 7.8.1. VersionSpace Learning
 7.8.2. Probably Approximately Correct Learning
 7.9. Review
 7.10. References and Further Reading
 7.11. Exercises
 III. Reasoning, Learning and Acting with Uncertainty
 8. Reasoning with Uncertainty
 8.1. Probability
 8.1.1. Semantics of Probability
 8.1.2. Axioms for Probability
 8.1.3. Conditional Probability
 8.1.4. Expected Values
 8.1.5. Information
 8.2. Independence
 8.3. Belief Networks
 8.3.1. Observations and Queries
 8.3.2. Constructing Belief Networks
 8.4. Probabilistic Inference
 8.4.1. Variable Elimination for Belief Networks
 8.4.2. Representing Conditional Probabilities and Factors
 8.5. Sequential Probability Models
 8.5.1. Markov Chains
 8.5.2. Hidden Markov Models
 8.5.3. Algorithms for Monitoring and Smoothing
 8.5.4. Dynamic Belief Networks
 8.5.5. Time Granularity
 8.5.6. Probabilistic Models of Language
 8.6. Stochastic Simulation
 8.6.1. Sampling from a Single Variable
 8.6.2. Forward Sampling in Belief Networks
 8.6.3. Rejection Sampling
 8.6.4. Likelihood Weighting
 8.6.5. Importance Sampling
 8.6.6. Particle Filtering
 8.6.7. Markov Chain Monte Carlo
 8.7. Review
 8.8. References and Further Reading
 8.9. Exercises
 9. Planning with Uncertainty
 9.1. Preferences and Utility
 9.1.1. Axioms for Rationality
 9.1.2. Factored Utility
 9.1.3. Prospect Theory
 9.2. OneOff Decisions
 9.2.1. SingleStage Decision Networks
 9.3. Sequential Decisions
 9.3.1. Decision Networks
 9.3.2. Policies
 9.3.3. Variable Elimination for Decision Networks
 9.4. The Value of Information and Control
 9.5. Decision Processes
 9.5.1. Policies
 9.5.2. Value Iteration
 9.5.3. Policy Iteration
 9.5.4. Dynamic Decision Networks
 9.5.5. Partially Observable Decision Processes
 9.6. Review
 9.7. References and Further Reading
 9.8. Exercises
 10. Learning with Uncertainty
 10.1. Probabilistic Learning
 10.1.1. Learning Probabilities
 10.1.2. Probabilistic Classifiers
 10.1.3. MAP Learning of Decision Trees
 10.1.4. Description Length
 10.2. Unsupervised Learning
 10.2.1. kMeans
 10.2.2. Expectation Maximization for Soft Clustering
 10.3. Learning Belief Networks
 10.3.1. Learning the Probabilities
 10.3.2. Hidden Variables
 10.3.3. Missing Data
 10.3.4. Structure Learning
 10.3.5. General Case of Belief Network Learning
 10.4. Bayesian Learning
 10.5. Review
 10.6. References and Further Reading
 10.7. Exercises
 11. Multiagent Systems
 11.1. Multiagent Framework
 11.2. Representations of Games
 11.2.1. Normal Form Games
 11.2.2. Extensive Form of a Game
 11.2.3. Multiagent Decision Networks
 11.3. Computing Strategies with Perfect Information
 11.4. Reasoning with Imperfect Information
 11.4.1. Computing Nash Equilibria
 11.5. Group Decision Making
 11.6. Mechanism Design
 11.7. Review
 11.8. References and Further Reading
 11.9. Exercises
 12. Learning to Act
 12.1. Reinforcement Learning Problem
 12.2. Evolutionary Algorithms
 12.3. Temporal Differences
 12.4. Qlearning
 12.5. Exploration and Exploitation
 12.6. Evaluating Reinforcement Learning Algorithms
 12.7. OnPolicy Learning
 12.8. ModelBased Reinforcement Learning
 12.9. Reinforcement Learning with Features
 12.9.1. SARSA with Linear Function Approximation
 12.10. Multiagent Reinforcement Learning
 12.10.1. PerfectInformation Games
 12.10.2. Learning to Coordinate
 12.11. Review
 12.12. References and Further Reading
 12.13. Exercises
 Note continued:
 IV. Reasoning, Learning and Acting with Individuals and Relations
 13. Individuals and Relations
 13.1. Exploiting Relational Structure
 13.2. Symbols and Semantics
 13.3. Datalog: A Relational Rule Language
 13.3.1. Semantics of Ground Datalog
 13.3.2. Interpreting Variables
 13.3.3. Queries with Variables
 13.4. Proofs and Substitutions
 13.4.1. Instances and Substitutions
 13.4.2. Bottomup Procedure with Variables
 13.4.3. Unification
 13.4.4. Definite Resolution with Variables
 13.5. Function Symbols
 13.5.1. Proof Procedures with Function Symbols
 13.6. Applications in Natural Language
 13.6.1. Using Definite Clauses for ContextFree Grammars
 13.6.2. Augmenting the Grammar
 13.6.3. Building Structures for Nonterminals
 13.6.4. Canned Text Output
 13.6.5. Enforcing Constraints
 13.6.6. Building a Natural Language Interface to a Database
 13.6.7. Limitations
 13.7. Equality
 13.7.1. Allowing Equality Assertions
 13.7.2. Unique Names Assumption
 13.8. Complete Knowledge Assumption
 13.8.1. Complete Knowledge Assumption Proof Procedures
 13.9. Review
 13.10. References and Further Reading
 13.11. Exercises
 14. Ontologies and KnowledgeBased Systems
 14.1. Knowledge Sharing
 14.2. Flexible Representations
 14.2.1. Choosing Individuals and Relations
 14.2.2. Graphical Representations
 14.2.3. Classes
 14.3. Ontologies and Knowledge Sharing
 14.3.1. Uniform Resource Identifiers
 14.3.2. Description Logic
 14.3.3. TopLevel Ontologies
 14.4. Implementing KnowledgeBased Systems
 14.4.1. Base Languages and Metalanguages
 14.4.2. A Vanilla MetaInterpreter
 14.4.3. Expanding the Base Language
 14.4.4. DepthBounded Search
 14.4.5. MetaInterpreter to Build Proof Trees
 14.4.6. Delaying Goals
 14.5. Review
 14.6. References and Further Reading
 14.7. Exercises
 15. Relational Planning, Learning, and Probabilistic Reasoning
 15.1. Planning with Individuals and Relations
 15.1.1. Situation Calculus
 15.1.2. Event Calculus
 15.2. Relational Learning
 15.2.1. Structure Learning: Inductive Logic Programming
 15.2.2. Learning Hidden Properties: Collaborative Filtering
 15.3. Statistical Relational Artificial Intelligence
 15.3.1. Relational Probabilistic Models
 15.4. Review
 15.5. References and Further Reading
 15.6. Exercises
 V. Retrospect and Prospect
 16. Retrospect and Prospect
 16.1. Dimensions of Complexity Revisited
 16.2. Social and Ethical Consequences
 16.3. References and Further Reading
 16.4. Exercises
 A. Mathematical Preliminaries and Notation
 A.1. Discrete Mathematics
 A.2. Functions, Factors and Arrays
 A.3. Relations and the Relational Algebra. A.1. Discrete Mathematics
 A.2. Functions, Factors and Arrays
 A.3. Relations and the Relational Algebra.
(source: Nielsen Book Data)
 Online
Engineering Library (Terman)
Engineering Library (Terman)  Status 

Stacks  
Q342 .P66 2017  Unknown 
 Berlin : Springer, c. 1996.
 Description
 Book — 1 online resource (IX, 416 pages) : illustrations Digital: text file.PDF.
 Summary

 Hyper tableaux
 An algorithm for the retrieval of unifiers from discrimination trees
 Building proofs or counterexamples by analogy in a resolution framework
 What you always wanted to know about rigid Eunification
 Labelled proofs for quantified modal logic
 A uniform tableaux method for nonmonotonic modal logics
 Design and implementation of diagnostic strategies using modal logic
 A modal action logic based framework for organization specification and analysis
 McCarthy's idea
 Strong and explicit negation in nonmonotonic reasoning and logic programming
 Only persistence makes nonmonotonicity monotonous
 Orderingbased representations of rational inference
 Semirepresentability of default theories in rational default logic
 A query answering algorithm for Lukaszewicz' general open default theory
 Infinitary default logic for specification of nonmonotonic reasoning
 A system for computing constrained default logic extensions
 The Oz programming model
 An abductive framework for negation in disjunctive logic programming
 Characterizing DWFS: Confluence and iterated GCWA
 Modules and specifications
 Logic programming with integrity constraints
 Temporal reasoning over linear discrete time
 Similarity saturation for first order linear temporal logic with UNLESS
 Carving Up space: Steps towards construction of an absolutely complete theory of spatial regions
 Informational logic for automated reasoning
 Extensions for open default theories via the domain closure assumption
 Revising and updating using a backup semantics
 A simple signed system for paraconsistent reasoning.
19. Intelligent behavior in animals and robots [1993]
 McFarland, David.
 Cambridge, Mass. : MIT Press, ©1993.
 Description
 Book — 1 online resource (xi, 308 pages) : illustrations
 Summary

 Introduction
 1. Intelligent Behavior
 2. Rational Behavior
 3. Utility
 4. State and Cost
 5. Design and Decision
 6. Motivation and Autonomy
 7. Goals and Behavior
 8. Accomplishing Tasks
 9. Prerequisites for an Autonomous Robot
 10. The Goal Function in Robot Architecture
 11. Animal and Robot Learning
 12. Conclusions
 Bibliography
 Index.
(source: Nielsen Book Data)
 Portuguese Conference on Artificial Intelligence (5th : 1991 : Albufeira, Portugal)
 Berlin : Springer, ©1991.
 Description
 Book — 1 online resource (viii, 292 pages) : illustrations
 Summary

 Solving linear constraints on finite domains through parsing
 Constraint solving in finite domains under user control
 A new method for solving linear constraints on the natural numbers
 A constraintbased fuzzy inference system
 A constraintbased language for querying taxonomic systems
 Heuristic parsing and search space pruning
 Waveshaping in multiprocessor bidirectional heuristic state space search
 The extended stable models of contradiction removal semantics
 Modeling a rational cognitive agent in SNePS
 Semantics of property inheritance in a hierarchic system with explicit negation
 Time in confluences: Dealing with delays for consistencychecking
 A temporal representation for imperatively structured plans of actions
 Maximal intervals: An approach to temporal reasoning
 Consistency driven planning
 An efficient approach to planning in assembly tasks
 Towards a theory of the repair process
 Declarative source debugging
 A neural approach to data compression and classification
 Generalization for a propositional calculus: a constraintsbased approach
 Adaptive learning using a qualitative feedback loop.
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