Intelligence through simulated evolution : forty yeays of evolutionary programming
著者
書誌事項
Intelligence through simulated evolution : forty yeays of evolutionary programming
（Wiley series on intelligent systems / James Albus, Alexander Meystel and Lotfi A. Zadeh (eds.)）
Wiley, 1999
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注記
"A Wiley-Interscience publication."
Includes bibliographical references (p. 143-156) and index
内容説明・目次
内容説明
A unique, one-stop reference to the history, technology, and application of evolutionary programming Evolutionary programming has come a long way since Lawrence Fogel first proposed in 1961 that intelligence could be modeled on the natural process of evolution. Efforts to apply this innovative approach to artificial intelligence have also evolved over the years, and the advent of fast desktop computers capable of solving complex computational problems has spawned an explosion of interest in the field. Offering the unique perspective of one of the inventors of evolutionary programming, this remarkable work traces forty years of developments in the field. Dr. Fogel consolidates a wealth of information and hard-to-find figures from across the literature, providing comprehensive coverage of the evolutionary programming approach to simulated evolution. This includes both an updated, condensed version of his bestselling 1966 work, Artificial Intelligence Through Simulated Evolution (with Owens and Walsh), and a thorough discussion of the history, technology, and methods of machine learning from 1970 to the present.
This important resource features clear, up-to-date explanations of how the simulation of evolutionary processes allows machines to learn to solve new problems in new ways. And it helps readers make the leap to generating intelligent systems-extending the discussion to neural networks, fuzzy logic, and genetic algorithms development. Engineers and computer scientists in all areas of machine learning will gain invaluable insight into existing and emerging applications and obtain ample ideas to draw upon in future research.
目次
- Genesis
- motivation
- prediction experiments
- pattern recognition and classification
- control system design
- extension of early evolutionary programming concepts
- competitive goal-seeking
- some implications
- diversification
- two-person gaming against nonminimax players
- coevolution, pursuit and evasion
- modeling time series
- pattern recognition
- simulated ecosystems and the nature of intelligence
- sequence induction with deterministic automata
- revising and extending early evolutionary programming
- routing problems
- comparing crossover, inversion, and mutation
- specialisations
- finding structure in data
- self-adaptation
- evolving neural networks
- evolving S-expression and multiple interacting programs
- games
- other applications.
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