Advances In Learning Classifier Systems学习分类器系统进展

出版时间：2001-10  出版社：1 edition (2001年10月1日)  作者：Pier L. Lanzi  页数：272  

内容概要

This subseries of Lecture Notes in Computer Science reports new devel-opments in artificial intelligence research and teaching,quickly,informally,and at a high level,The timeliness of a manuscript is more important than its form,which may be unfinished or tentative.The type of material considered for publication includes.    -drafts of original papers or monographs.    -technical reports of high quality and broad interest,    -advanced-level lectures,    -reports of meetings,provided they are of exceptional interest and focused on a single topic.    Publication of Lecture Notes is inteded as service to the computer science community in that the publisher Springer-Verlag offers global distribution of documents which would otherwise have a restricted readership.One pub-lished and copyrighted they can be cited in the scientific literature.

书籍目录

Ⅰ Theory  An Artificial Economy of Post Production Systems  Simple Markov Models of the Genetic Algorithm in Classifier Systems：Accuracy-Based Fitness  Simple Markov Models of the Genetic Algorithm in Classifier Systems：Multi-step Tasks  Probability-Enhanced Predictions in the Anticipatory Classifier System  YACS：Combining Dynamic Programming with Generalization in Classifier Systems  A Self-Adaptive Classifier System  What Makes a Problem Hard for XCS?Ⅱ  Applications  Applying a Learning Classifier System to Mining Explanatory and Predictive Models from a Large Clinical Database  Strength and Money：An LC S Approach to Increasing Returns  Using Classifier Systems as Adaptive Expert Systems for Control  Mining Oblique Data with XCSⅢ Advanced Architectures  A Study on the Evolution of Learning Classifier Systems  Learning Classifier Systems Meet Multiagent EnvironmentsⅣ The Bibliography  A Bigger Learning Classifier Systems BibliographyⅤ Appendix  An Algorithmic Description of XCSAuthor Index

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