<電子ブック>
Evolutionary Computing : AISB Workshop, Leeds, U.K., April 11 - 13, 1994. Selected Papers / edited by Terence C. Fogarty
(Lecture Notes in Computer Science. ISSN:16113349 ; 865)
版 | 1st ed. 1994. |
---|---|
出版者 | Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer |
出版年 | 1994 |
本文言語 | 英語 |
大きさ | XII, 340 p : online resource |
著者標目 | Fogarty, Terence C editor SpringerLink (Online service) |
件 名 | LCSH:Artificial intelligence LCSH:Computer science LCSH:Algorithms LCSH:Pattern recognition systems LCSH:Bioinformatics LCSH:Biomathematics FREE:Artificial Intelligence FREE:Theory of Computation FREE:Algorithms FREE:Automated Pattern Recognition FREE:Computational and Systems Biology FREE:Mathematical and Computational Biology |
一般注記 | Formal memetic algorithms -- A statistical mechanical formulation of the dynamics of genetic algorithms -- Evolutionary stability in simple classifier systems -- Nonbinary transforms for genetic algorithm problems -- Enhancing evolutionary computation using analogues of biological mechanisms -- Exploiting mate choice in evolutionary computation: Sexual selection as a process of search, optimization, and diversification -- An empirical comparison of selection methods in evolutionary algorithms -- An evolution strategy and genetic algorithm hybrid: An initial implementation and first results -- Genetic algorithms and directed adaptation -- Genetic algorithms and neighbourhood search -- A unified paradigm for parallel Genetic Algorithms -- Distributed coevolutionary genetic algorithms for multi-criteria and multi-constraint optimisation -- Inductive operators and rule repair in a hybrid genetic learning system: Some initial results -- Adaptive learning of a robot arm -- Co-evolving Co-operative populations of rules in learning control systems -- Learning anticipatory behaviour using a delayed action classifier system -- Applying a restricted mating policy to determine state space niches using immediate and delayed reinforcement -- A comparison between two architectures for searching and learning in maze problems -- Fast practical evolutionary timetabling -- Optimising a presentation timetable using evolutionary algorithms -- Genetic algorithms and flowshop scheduling: towards the development of a real-time process control system -- Genetic algorithms for digital signal processing -- Complexity reduction using expansive coding -- The application of genetic programming to the investigation of short, noisy, chaotic data series This volume is based on the Workshop on Evolutionary Computing held in Leeds, U.K. in April 1994 under the sponsorship of the Society for the Study of Artificial Intelligence and Simulation of Behaviour. In addition to the 22 best papers presented at the workshop, there are two invited contributions by Ray Paton and Colin Reever. The volume addresses several aspects of evolutionary computing, particularly genetic algorithms, and its applications, for example in search, robotics, signal processing, machine learning, and scheduling. The papers are organized in sections on theoretical and biological foundations, techniques, classifier systems, and applications HTTP:URL=https://doi.org/10.1007/3-540-58483-8 |
目次/あらすじ
所蔵情報を非表示
電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
電子ブック | オンライン | 電子ブック |
|
|
Springer eBooks | 9783540489993 |
|
電子リソース |
|
EB00225533 |