Efficient learning and planning within the Dyna framework

Jing Peng, Ronald J. Williams

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations

Abstract

Sutton's Dyna framework provides a novel and computationally appealing way to create integrated learning, planning, and reacting systems. Examined here is a class of strategies designed to enhance the learning and planning power of Dyna systems by increasing their computational efficiency. The benefit of using these strategies is demonstrated on some simple abstract learning tasks.

Original languageEnglish
Title of host publication1993 IEEE International Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Pages168-174
Number of pages7
ISBN (Print)0780312007
StatePublished - 1 Jan 1993
Event1993 IEEE International Conference on Neural Networks - San Francisco, CA, USA
Duration: 28 Mar 19931 Apr 1993

Publication series

Name1993 IEEE International Conference on Neural Networks

Other

Other1993 IEEE International Conference on Neural Networks
CitySan Francisco, CA, USA
Period28/03/931/04/93

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