Using advice to transfer knowledge acquired in one reinforcement learning task to another

Lisa Torrey, Trevor Walker, Jude Shavlik, Richard Maclin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Scopus citations

Abstract

We present a method for transferring knowledge learned in one task to a related task. Our problem solvers employ reinforcement learning to acquire a model for one task. We then transform that learned model into advice for a new task. A human teacher provides a mapping from the old task to the new task to guide this knowledge transfer. Advice is incorporated into our problem solver using a knowledge-based support vector regression method that we previously developed. This advice-taking approach allows the problem solver to refine or even discard the transferred knowledge based on its subsequent experiences. We empirically demonstrate the effectiveness of our approach with two games from the RoboCup soccer simulator: KeepAway and BreakAway. Our results demonstrate that a problem solver learning to play BreakAway using advice extracted from KeepAway outperforms a problem solver learning without the benefit of such advice.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages412-424
Number of pages13
DOIs
StatePublished - 2005
Externally publishedYes
Event16th European Conference on Machine Learning, ECML 2005 - Porto, Portugal
Duration: Oct 3 2005Oct 7 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3720 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other16th European Conference on Machine Learning, ECML 2005
CountryPortugal
CityPorto
Period10/3/0510/7/05

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