Advances in the Evolutionary Synthesis of Intelligent Agents

by Mukesh Patel, Vasant Honavar and Karthik Balakrishnan (Eds.)

• ISBN13: 9780262162012
• ISBN10: 0262162016
• Format: Hardcover
• Copyright: 2001-03-05
• Publisher: Bradford Books

Summary

Among the first uses of the computer was the development of programs to model perception, reasoning, learning, and evolution. Further developments resulted in computers and programs that exhibit aspects of intelligent behavior. The field of artificial intelligence is based on the premise that thought processes can be computationally modeled. Computational molecular biology brought a similar approach to the study of living systems. In both cases, hypotheses concerning the structure, function, and evolution of cognitive systems (natural as well as synthetic) take the form of computer programs that store, organize, manipulate, and use information. Systems whose information processing structures are fully programmed are difficult to design for all but the simplest applications. Real-world environments call for systems that are able to modify their behavior by changing their information processing structures. Cognitive and information structures and processes, embodied in living systems, display many effective designs for biological intelligent agents. They are also a source of ideas for designing artificial intelligent agents. This book explores a central issue in artificial intelligence, cognitive science, and artificial life: how to design information structures and processes that create and adapt intelligent agents through evolution and learning. The book is organized around four topics: the power of evolution to determine effective solutions to complex tasks, mechanisms to make evolutionary design scalable, the use of evolutionary search in conjunction with local learning algorithms, and the extension of evolutionary search in novel directions.

Table of Contents

Contributors	ix
Preface	xiii
Evolutionary and Neural Synthesis of Intelligent Agents	1	(28)
Karthik Balakrishnan
Vasant Honavar
Cellular Encoding for Interactive Evolutionary Robotics	29	(36)
Frederic Gruau
Kameel Quatramaran
The Emergence of Communication Through Synthetic Evolution	65	(26)
Bruce J. MacLennan
Optimization of Classifiers Using Genetic Algorithms	91	(18)
J. J. Merelo
A. Prieto
F. Moran
Evolving Neuro-Controllers and Sensors for Artificial Agents	109	(44)
Karthik Balakrishnan
Vasant Honavar
Combined Biological Metaphors	153	(32)
Egbert J. W. Boers
Ida G. Sprinkhuizen-Kuyper
Evolutionary Neurogenesis Applied to Mobile Robotics	185	(30)
Oliver Michel
Development in Neural Networks	215	(32)
Domenico Parisi
Stefano Nolfi
Evolution and Learning in Radial Basis Function Neural Networks - A Hybrid Approach	247	(26)
Brian Carse
Terence C. Fogarty
John C. W. Sullivan
Co-Evolution and Ontogenetic Change in Competing Robots	273	(34)
Dario Floreano
Stefano Nolfi
Francesco Mondada
Goal Directed Adaptive Behavior in Second-Order Neural Networks: Learning and Evolving in the MAXSON Architecture	307	(30)
Frederick L. Crabbe
Michael G. Dyer
Evolving Heterogeneous Neural Agents by Local Selection	337	(30)
Filippo Menczer
W. Nick Street
Melania Degeratu
Learning Sequential Decision Tasks through Symbiotic Evolution of Netural Networks	367	(16)
David E. Moriarty
Risto Miikkulainen
From Evolving a Single Neural Network to Evolving Neural Network Ensembles	383	(46)
Xin Yao
Yong Liu
Evolutionary Synthesis of Bayesian Networks for Optimization	429	(28)
Heinz Muhlenbein
Thilo Mahnig
Index	457