Evolutionary Computation for Modeling and Optimization - Daniel Ashlock

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Résumé :
Evolutionary Computation for Optimization and Modeling is an introduction to evolutionary computation, selectionist algorithms that operate on populations of structures. It includes over 100 experiments and over 700 homework problems that introduce the topic with an application-oriented approach. Engineering, computer science, and applied math students will find the book a useful guide to using evolutionary algorithms as a problem solving tool. No previous familliarity with evolutionary computation is assumed. The topics 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. The problem oriented approach of the book makes it a good text for engineering of computer science application classes....

Biographie:
Dr. Eun-Youn Kim is a mathematician with a background in graph theory and evolutionary game theory, having worked extensively on the issue of representation in the design of gameplaying agents. Dr. Kim received her Ph.D. in mathematics from Iowa State University. She has been employed at the National Institute of Mathematical Sciences and the Korea Institute of Bioscience and Biotechnology in Korea. Dr. Kims research interests include broad interests in evolutionary computation applied to game playing and network modeling in biological systems. She is a member of the IEEE Computational Intelligence Societies technical committee on games and has helped organize international games conferences. Dr. Kim is currently employed by the department of basic science in Hanbat National University in South Korea.Dr. Daniel Ashlock is a professor of mathematics at the University of Guelph in Ontario, Canada. Dr. Ashlock received his Ph.D. in mathematics from Caltech with a focus in algebraic combinatorics. He was employed at Iowa State University before moving to Canada. Dr. Ashlock works on representation issues in evolutionary computation including games, optimization, bioinformatics, and theoretical biology. He holds the Bioinformatics Chair in the Department of Mathematics and Statistics at Guelph and serves on the editorial board of the IEEE Transactions on Evolutionary Computation, the IEEE Transactions on Games, The IEEE/ACM Transactions on Bioinformatics and Computational Biology, Biosystems, and Game and Puzzle Design. Dr. Ashlock serves on the IEEE Computational Intelligence Societies technical committees on games and bioinformatics and biomedical engineering....

Sommaire:
An Overview of Evolutionary Computation.- Designing Simple Evolutionary Algorithms.- Optimizing Real-Valued Functions.- Sunburn: Coevolving Strings.- Small Neural Nets : Symbots.- Evolving Finite State Automata.- Ordered Structures.- Plus-One-Recall-Store.- Fitting to Data.- Tartarus: Discrete Robotics.- Evolving Logic Functions.- ISAc List: Alternative Genetic Programming.- Graph-Based Evolutionary Algorithms.- Cellular Encoding.- Application to Bioinformatics.