Skill acquisition via transfer learning and advice taking

Lisa Torrey, Jude Shavlik, Trevor Walker, Richard Maclin

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

36 Scopus citations

Abstract

We describe a reinforcement learning system that transfers skills from a previously learned source task to a related target task. The system uses inductive logic programming to analyze experience in the source task, and transfers rules for when to take actions. The target task learner accepts these rules through an advice-taking algorithm, which allows learners to benefit from outside guidance that may be imperfect. Our system accepts a human-provided mapping, which specifies the similarities between the source and target tasks and may also include advice about the differences between them. Using three tasks in the RoboCup simulated soccer domain, we demonstrate that this system can speed up reinforcement learning substantially.

Original languageEnglish (US)
Title of host publicationMachine Learning
Subtitle of host publicationECML 2006 - 17th European Conference on Machine Learning, Proceedings
PublisherSpringer Verlag
Pages425-436
Number of pages12
ISBN (Print)354045375X, 9783540453758
DOIs
StatePublished - 2006
Externally publishedYes
Event17th European Conference on Machine Learning, ECML 2006 - Berlin, Germany
Duration: Sep 18 2006Sep 22 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4212 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other17th European Conference on Machine Learning, ECML 2006
CountryGermany
CityBerlin
Period9/18/069/22/06

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