Classifier Fitness Based on Accuracy

Author:

Wilson Stewart W.1

Affiliation:

1. The Rowland Institute for Science 100 Edwin H. Land Blvd. Cambridge, MA 02142

Abstract

In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier's fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier's fitness is given by a measure of the prediction's accuracy. The system executes the genetic algorithm in niches defined by the match sets, instead of panmictically. These aspects of XCS result in its population tending to form a complete and accurate mapping X × A → P from inputs and actions to payoff predictions. Further, XCS tends to evolve classifiers that are maximally general, subject to an accuracy criterion. Besides introducing a new direction for classifier system research, these properties of XCS make it suitable for a wide range of reinforcement learning situations where generalization over states is desirable.

Publisher

MIT Press - Journals

Subject

Computational Mathematics

Cited by 784 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Evolutionary Regression and Modelling;Handbook of Evolutionary Machine Learning;2023-11-02

2. Discovering Rules for Rule-Based Machine Learning with the Help of Novelty Search;SN Computer Science;2023-10-12

3. Phishing Detection with Browser Extension Based on Machine Learning;2023 18th Asia Joint Conference on Information Security (AsiaJCIS);2023-08-15

4. Evaluation and Exploration of Machine Learning and Convolutional Neural Network Classifiers in Detection of Lung Cancer from Microarray Gene—A Paradigm Shift;Bioengineering;2023-08-06

5. Towards Principled Synthetic Benchmarks for Explainable Rule Set Learning Algorithms;Proceedings of the Companion Conference on Genetic and Evolutionary Computation;2023-07-15

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3