Improving Reinforcement Learning Agents Using Genetic Algorithms

被引：0

作者：

Beigi, Akram ^{[1
]}

Parvin, Hamid ^{[1
]}

Mozayani, Nasser ^{[1
]}

Minaei, Behrouz ^{[1
]}

机构：

[1] Iran Univ Sci & Technol, Comp Engn Sch, Tehran, Iran

来源：

ACTIVE MEDIA TECHNOLOGY | 2010年 / 6335卷

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper a new Reinforcement Learning algorithm was proposed. Q learning is a useful algorithm for agent learning in nondeterministic environment but it is a time consuming algorithm. The presented work applies an evolutionary algorithm for improving Reinforcement Learning algorithm.

引用

页码：330 / 337

页数：8

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