学习分类器系统进展/会议录 Advances in learning classifier systems
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作者： Pier L. Lanzi著
出 版 社： 湖南文艺出版社
出版时间： 2002-12-1字数：版次： 1页数： 229印刷时间： 2006/12/01开本：印次：纸张： 胶版纸I S B N ： 9783540437932包装： 平装编辑推荐
The LNAI series reports state-of-the-art results in artificial intelligence re-search，development， and education， at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community， with numerous individuals， as well as with prestigious organizations and societies，LNAI has grown into the most comprehensive artificial intelligence research forum available.
The scope of LNAI spans the whole range of artificial intelligence and intelli-gent information processing including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes.
—proceedings （published in time for the respective conference）
—post-proceedings （consisting of thoroughly revised final full papers）
—research monographs（which may be based on PhD work）.
内容简介
This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Learning Classifier Systems, IWLCS 2001, held in San Francisco, CA, USA, in July 2001.The 12 revised full papers presented together with a special paper on a formal description of ACS have gone through two rounds of reviewing and improvement. The first part of the book is devoted to theoretical issues of learning classifier systems including the influence of exploration strategy, self-adaptive classifier systems, and the use of classifier systems for social simulation. The second part is devoted to applications in various fields such as data mining, stock trading, and power distributionn networks.
目录
I Theory
Biasing Exploration in an Anticipatory Learning Classifier System
An Incremental Multiplexer Problem and Its Uses in Classifier Systen Research
A Minimal Model of Communication for a Multi-agent Classifier System
A Representation for Accuracy-Based Assessment of Classifier System:Prediction Performance
A Self-Adaptive XCS
Two Views of Classifier Systems
Social Simulation Using a Multi-agent Model Based on Classifier Systems:The Emergence of Vacillating Behaviour in the "El Farol" Bar Problem
II Applications
XCS and GALE: A Comparative Study of Two Learning Classifier System on Data Mining
A Preliminary Investigation of Modified XCS as a Generic Data Minin Tool
Explorations in LCS Models of Stock Trading
On-Line Approach for Loss Reduction in Electric Power Distribution Networks Using Learning Classifier Systems
Compact Rulesets from XCSI
III Appendix
An Algorithmic Description of ACS2
Author Index
