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• Engineering design applications
• general design Applications
• design representation issues
• manufacturing applications
• multi-objective satisfaction
• algorithm comparison and development
• neural nets and hybrid systems.
• (source: Nielsen Book Data)

This collection of selected papers from the Fourth International Conference on Adaptive Computing in Design and Manufacture (ACDM0) represents a cross-section of the state-of-the art relating to the integration of advanced stochastic search, exploration and optimisation techniques with complex problem areas relating to various aspects of design and manufacturing processes. The Conference, held in the Sherwell Conference Centre at the University of Plymouth, Devon, UK in April, 2000, is a well-established biennial event supported by several UK Engineering Institutions and recognised by the International Society for Genetic and Evolutionary Computation as a mainstream event. The conference continues to attract an international audience of leading researchers and practitioners in the field. Aerospace, mechanical, thermal and structural design are among the subjects treated. In terms of manufacturing processes, cell formation, facility design, system control and robotics are addressed. In most cases, results from their application to or integration with real-world industrial problems are very much in evidence and conclusions relating to the overall utility of the various techniques across a diverse spectrum of problem areas are available. Evolutionary computing research and its application provides the mainstay in the great majority of papers. In the tradition of the ACDM series, papers utilising neural computing technologies and related computational intelligence techniques within the design/manufacture environments have also been included. The collection further illustrates the increasing uptake of these technologies in terms of academic research, academic and industrial collaboration and industrial practice. It is apparent that application strategies are becoming increasingly sophisticated as the powerful data processing capabilities of the technologies become more apparent and their increasing potential leads to integration with more complex problem areas so the book will be of particular interest to both design and computer science research communities in addition to those industrial organisations that are either already including these technologies in day-to-day working practice or that wish to familiarise themselves with the potential utility of their application further.
(source: Nielsen Book Data)

• The volume presents 22 revised full papers carefully selected for inclusion together with an invited survey on the state-of-the-art in scatter search by Fred Glover. The papers are organized in topical sections on genetic-algorithm operators, applications in various areas, theoretical issues, methodologies, and evolvable hardware and robotics.
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-conference proceedings of the Third European Conference on Artificial Evolution, AE '97, held in Nimes, France, in October 1997. The volume presents 22 revised full papers carefully selected for inclusion together with an invited survey on the state-of-the-art in scatter search by Fred Glover. The papers are organized in topical sections on genetic-algorithm operators, applications in various areas, theoretical issues, methodologies, and evolvable hardware and robotics.
(source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-conference proceedings of the 4th European Conference on Artificial Evolution, AE '99, held in Dunkerque, France in November 1999. The 20 revised full papers presented together with one invited paper were carefully selected during two rounds of reviewing from initially more than 40 papers submitted. The book is divided in topical sections on genetic operators and theoretical models, applications, agents and cooperation, and heuristics and outlook.
(source: Nielsen Book Data)

• Practical Genetic Algorithms.- Real-World Application: Routing Problem.- Elitist Compact Genetic Algorithms.- Real-coded Bayesian Optimization Algorithm.- Multiobjective Real-coded Bayesian Optimization Algorithm.- Conclusions.
• (source: Nielsen Book Data)

Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. This book provides effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms.
(source: Nielsen Book Data)

• Practical Genetic Algorithms.- Real-World Application: Routing Problem.- Elitist Compact Genetic Algorithms.- Real-coded Bayesian Optimization Algorithm.- Multiobjective Real-coded Bayesian Optimization Algorithm.- Conclusions.
• (source: Nielsen Book Data)

Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. This book provides effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms.
(source: Nielsen Book Data)

This volume contains the best carefully revised full papers selected from the presentations accepted for the AI '93 and AI '94 Workshop on Evolutionary Computation held in Australia. The 21 papers included cover a wide range of topics in the field of evolutionary computation, from constrained function optimization to combinatorial optimization, from evolutionary programming to genetic programming, from robotic strategy learning to co-evolutionary game strategy learning. The papers reflect important recent progress in the field; more than half of the papers come from overseas.
(source: Nielsen Book Data)

This book contains a selection of papers presented at a workshop on evolutionary computing sponsored by the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB, at the University of Sussex in Brighton, UK, in April 1996.The 22 revised full papers included in the book, together with one invited contribution, were carefully reviewed by the program committee. Twelve contributions investigate applications of evolutionary computing in various areas, such as learning, scheduling, searching, genetic programming, image processing, and robotics. Eleven papers are devoted to evolutionary computing theory and techniques.
(source: Nielsen Book Data)

This book contains a selection of papers presented at a workshop on evolutionary computing sponsored by the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB, at the University of Sussex in Brighton, UK, in April 1996.The 22 revised full papers included in the book, together with one invited contribution, were carefully reviewed by the program committee. Twelve contributions investigate applications of evolutionary computing in various areas, such as learning, scheduling, searching, genetic programming, image processing, and robotics. Eleven papers are devoted to evolutionary computing theory and techniques.
(source: Nielsen Book Data)

• Simulating pricing behaviours using a genetic algorithm / Sue Bedingfield, Stephen Huxford, Yen Cheung
• Biologically inspired computational ecologies : a case study / Paul Devine, Ray Paton
• Modelling bounded rationality using evolutionary techniques / Bruce Edmonds, Scott Moss
• The abstract theory of evolution of the living / V.L. Kalmykov
• An evolutionary algorithm for single objective nonlinear constrained optimization problems / Hunter P. Albright, James P. Ignizio
• On recombinative sampling / Ian East
• The evolution of mutation, plasticity and culture in cyclically changing environments ; On the structure and transformation of landscapes / Tony Hirst
• Island model genetic algorithms and linearly separable problems / Darrell Whitley, Soraya Rana, Robert Heckendorn
• Empirical validation of the performance of a class of transient detector / Philip Jacob, Andrew Ball
• The construction and evaluation of decision trees : a comparison of evolutionary and concept learning methods / H. Kennedy ... [et al.]
• Parallel distributed genetic programming applied to the evolution of natural language recognisers / Riccardo Poli
• Scheduling planned maintenance of the South Wales region of the national grid / Bill Langdon
• Solving generic scheduling problems with a distributed genetic algorithm / Malcolm McIlhagga
• Directing the search of evolutionary and neighbourhood-search optimisers for the flowshop sequencing problem with an idle-time heuristic / Peter Ross, Andrew Tuson
• Multiobjective genetic algorithms for pump scheduling in water supply / Dragan Savic, Godfrey Walters, Martin Schwab
• Use of rules and preferences for schedule builders in genetic algorithms for production scheduling / Jane Shaw, Peter Fleming
• A voxel based approach to evolutionary shape optimisation / Peter Baron ... [et al.]
• Phase transition networks : a modelling technique supporting the evolution of autonomous agents' tactical and operational activities / Anthony Deakin, Derek Yates
• An evolutionary, agent-assisted strategy for conceptual design space decomposition / Ian Parmee, M. Beck
• Task scheduling with use of classifier systems / Franciszek Seredýnski.

This book constitutes the refereed post-workshop proceedings of the AISB International Workshop on Evolutionary Computing, held in Manchester, UK, in April 1997.The 22 strictly reviewed and revised full papers presented were selected for inclusion in the book after two rounds of refereeing. The papers are organized in sections on evolutionary approaches to issues in biology and economics, problem structure and finite landscapes, evolutionary machine learning and classifier systems, evolutionary scheduling, and more techniques and applications of evolutionary algorithms.
(source: Nielsen Book Data)

• Some combinatorial landscapes on which a genetic algorithm outperforms other stochastic iterative methods / Dave Corne and Peter Ross
• Maximum entropy analysis of genetic algorithm operators / Jonathan L. Shapiro and Adam Prügel-Bennett
• The ant colony metaphor for searching continuous design spaces / G. Bilchev and I.C. Parmee
• Broadcast based fitness sharing GA for conflict resolution among autonomous robots / Sadoyoshi Mikami, Yukinori Kakazu and Terence C. Fogarty
• An adaptive poly-parental recombination strategy / Jim Smith and T.C. Fogarty
• Neighbourhood seeding to reduce problem modality / A.J. Swann
• Specialized recombinative operators for timetabling problems / Edmund Burke, Dave Elliman and Rupert Weare
• The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms / Ben Paechter, Andrew Cumming and Henri Luchian
• Comparing genetic algorithms, simulated annealing, and stochastic hillclimbing on timetable problems / Peter Ross and Dave Corne
• Evolutionary learning in computational ecologies : an application to adaptive, distributed routing in communication networks / Brian Carse, Terence C. Fogarty, and Alistair Munro
• The radio link frequency assignment problem : a case study using genetic algorithms / A. Kapsalis [and others]
• Scheduling planned maintenance of the national grid / W.B. Langdon
• Genetic operators and constraint handling for pipe network optimization / Dragan A. Savic and Godfrey A. Walters
• A multi-objective approach to constrained optimisation of gas supply networks : COMOGA method / Patrick D. Surry, Nicholas J. Radcliffe and Ian D. Boyd
• Ternary decision diagram optimisation of Reed-Muller logic functions using a genetic algorithm for variable and simplification rule ordering / J.F. Miller, P. Thomson and P.V.G. Bradbeer
• An evolutionary algorithm for parametric array signal processing / Dekum Yang and Stuart Flockton
• Constraints on task and search complexity in GA + NN models of learning and adaptive behaviour / Mukesh J. Patel
• Load balancing application of the genetic algorithm in a nonstationary environment / Frank Vavak, Terence C. Fogarty and Phillip Cheng
• Exploring some commercial applications of genetic programming / Gerald Robinson and Paul McIlroy.

This volume is based on the Workshop on Evolutionary Computing held in Sheffield, U.K., in April 1995 under the sponsorship of the Society for the Study of Artificial Intelligence and Simulation of Behavior (AISB). The 18 full papers presented were selected during a post-workshop refereeing meeting and chosen from 32 submissions for the workshop. The papers are organized in sections on evolutionary computing theory and techniques, timetabling, routing and scheduling, optimization, signal processing and control, and genetic programming. The collection of papers has a certain bias towards real world applications of evolutionary computing and particularly genetic algorithms.

• 1. Bio-inspired Algorithms
• 2. Data Classification Using Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron
• 3. Reconstruction of 3D Surfaces Using RBF Adjusted with PSO
• 4. Soft Computing Applications in Robot Vision
• 5. Soft Computing Applications inMobile Robotics
• 6. Particle Swarm Optimization to Improve Neural Identifiers for Discrete-time Unknown Nonlinear Systems
• 7. Bio-inspired Algorithms to Improve Neural Controllers for Discrete-time Unknown Nonlinear System
• 8. Final Remarks.
• (source: Nielsen Book Data)

Bio-inspired Algorithms for Engineering builds a bridge between the proposed bio-inspired algorithms developed in the past few decades and their applications in real-life problems, not only in an academic context, but also in the real world. The book proposes novel algorithms to solve real-life, complex problems, combining well-known bio-inspired algorithms with new concepts, including both rigorous analyses and unique applications. It covers both theoretical and practical methodologies, allowing readers to learn more about the implementation of bio-inspired algorithms. This book is a useful resource for both academic and industrial engineers working on artificial intelligence, robotics, machine learning, vision, classification, pattern recognition, identification and control.
(source: Nielsen Book Data)

• 1. Bio-inspired Algorithms
• 2. Data Classification Using Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron
• 3. Reconstruction of 3D Surfaces Using RBF Adjusted with PSO
• 4. Soft Computing Applications in Robot Vision
• 5. Soft Computing Applications inMobile Robotics
• 6. Particle Swarm Optimization to Improve Neural Identifiers for Discrete-time Unknown Nonlinear Systems
• 7. Bio-inspired Algorithms to Improve Neural Controllers for Discrete-time Unknown Nonlinear System
• 8. Final Remarks.
• (source: Nielsen Book Data)

Bio-inspired Algorithms for Engineering builds a bridge between the proposed bio-inspired algorithms developed in the past few decades and their applications in real-life problems, not only in an academic context, but also in the real world. The book proposes novel algorithms to solve real-life, complex problems, combining well-known bio-inspired algorithms with new concepts, including both rigorous analyses and unique applications. It covers both theoretical and practical methodologies, allowing readers to learn more about the implementation of bio-inspired algorithms. This book is a useful resource for both academic and industrial engineers working on artificial intelligence, robotics, machine learning, vision, classification, pattern recognition, identification and control.
(source: Nielsen Book Data)

• An Overview of Evolutionary Computation.- Designing Simple Evolutionary Algorithms.- Optimizing Real Values Functions.- Sunburn: Co-evolving Strings.- Small Neural Nets: Symbots.- Evolving Finite State Automata.- Ordered Structures.- Plus One Recall Store.- Fitting to Data.- Tartarus: Discrete Robotics.- Evolving Logic Gates.- ISAc lists: Alternative Genetic Programming.- Graph Based Evolutionary Algorithms.- Cellular Encoding.- Application to Bioinformatics.- Glossary.- Appendices.- References.- Index.
• (source: Nielsen Book Data)

"Evolutionary Computation for Optimization and Modeling" is an introduction to evolutionary computation, a field which includes genetic algorithms, evolutionary programming, evolution strategies, and genetic programming. The text is a survey of some application of evolutionary algorithms. It introduces mutation, crossover, design issues of selection and replacement methods, the issue of populations size, and the question of design of the fitness function. It also includes a methodological material on efficient implementation. Some of the other topics in this book include the design of simple evolutionary algorithms, applications to several types of optimization, evolutionary robotics, simple evolutionary neural computation, and several types of automatic programming including genetic programming. The book gives applications to biology and bioinformatics and introduces a number of tools that can be used in biological modeling, including evolutionary game theory. Advanced techniques such as cellular encoding, grammar based encoding, and graph based evolutionary algorithms are also covered. This book presents a large number of homework problems, projects, and experiments, with a goal of illustrating single aspects of evolutionary computation and comparing different methods. Its readership is intended for an undergraduate or first-year graduate course in evolutionary computation for computer science, engineering, or other computational science students. Engineering, computer science, and applied math students will find this book a useful guide to using evolutionary algorithms as a problem solving tool.
(source: Nielsen Book Data)

• Preface Acknowledgments Introduction Contrasting Representations for Maze Generation Dual Mazes Terrain Maps Cellular Automata Based Maps Decomposition, Tiling, and Assembly Bibliography Author's Biography.
• (source: Nielsen Book Data)

Automatic content generation is the production of content for games, web pages, or other purposes by procedural means. Search-based automatic content generation employs search-based algorithms to accomplish automatic content generation. This book presents a number of different techniques for search-based automatic content generation where the search algorithm is an evolutionary algorithm. The chapters treat puzzle design, the creation of small maps or mazes, the use of L-systems and a generalization of L-system to create terrain maps, the use of cellular automata to create maps, and, finally, the decomposition of the design problem for large, complex maps culminating in the creation of a map for a fantasy game module with designersupplied content and tactical features. The evolutionary algorithms used for the different types of content are generic and similar, with the exception of the novel sparse initialization technique are presented in Chapter 2. The points where the content generation systems vary are in the design of their fitness functions and in the way the space of objects being searched is represented. A large variety of different fitness functions are designed and explained, and similarly radically different representations are applied to the design of digital objects all of which are, essentially, maps for use in games.
(source: Nielsen Book Data)

• Preface Acknowledgments Introduction Contrasting Representations for Maze Generation Dual Mazes Terrain Maps Cellular Automata Based Maps Decomposition, Tiling, and Assembly Bibliography Author's Biography.
• (source: Nielsen Book Data)

Automatic content generation is the production of content for games, web pages, or other purposes by procedural means. Search-based automatic content generation employs search-based algorithms to accomplish automatic content generation. This book presents a number of different techniques for search-based automatic content generation where the search algorithm is an evolutionary algorithm. The chapters treat puzzle design, the creation of small maps or mazes, the use of L-systems and a generalization of L-system to create terrain maps, the use of cellular automata to create maps, and, finally, the decomposition of the design problem for large, complex maps culminating in the creation of a map for a fantasy game module with designersupplied content and tactical features. The evolutionary algorithms used for the different types of content are generic and similar, with the exception of the novel sparse initialization technique are presented in Chapter 2. The points where the content generation systems vary are in the design of their fitness functions and in the way the space of objects being searched is represented. A large variety of different fitness functions are designed and explained, and similarly radically different representations are applied to the design of digital objects all of which are, essentially, maps for use in games.
(source: Nielsen Book Data)

• Agents and Complex Systems.- Data Mining and Its Applications.- Evolutionary Algorithms and Optimization.- Intelligent Systems and their Applications.- Nature Inspired Creative Computing.- Smart Workspace and Image Processing.
• (source: Nielsen Book Data)

This PALO volume constitutes the Proceedings of the 19th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2015), held in Bangkok, Thailand, November 22-25, 2015. The IES series of conference is an annual event that was initiated back in 1997 in Canberra, Australia. IES aims to bring together researchers from countries of the Asian Pacific Rim, in the fields of intelligent systems and evolutionary computation, to exchange ideas, present recent results and discuss possible collaborations. Researchers beyond Asian Pacific Rim countries are also welcome and encouraged to participate. The theme for IES 2015 is "Transforming Big Data into Knowledge and Technological Breakthroughs". The host organization for IES 2015 is the School of Information Technology (SIT), King Mongkut's University of Technology Thonburi (KMUTT), and it is technically sponsored by the International Neural Network Society (INNS). IES 2015 is collocated with three other conferences; namely, The 6th International Conference on Computational Systems-Biology and Bioinformatics 2015 (CSBio 2015), The 7th International Conference on Advances in Information Technology 2015 (IAIT 2015) and The 10th International Conference on e-Business 2015 (iNCEB 2015), as a major part of series of events to celebrate the SIT 20th anniversary and the KMUTT 55th anniversary.
(source: Nielsen Book Data)