Improving reinforcement learning by using case based heuristics

Página do item simplificado
dc.contributor.authorReinaldo Bianchi
dc.contributor.authorROS, R.
dc.contributor.authorLOPES, DE M. R.
dc.contributor.authorOrcidhttps://orcid.org/0000-0001-9097-827X
dc.date.accessioned2022-01-12T22:04:35Z
dc.date.available2022-01-12T22:04:35Z
dc.date.issued2009-07-23
dc.description.abstractThis work presents a new approach that allows the use of cases in a case base as heuristics to speed up Reinforcement Learning algorithms, combining Case Based Reasoning (CBR) and Reinforcement Learning (RL) techniques. This approach, called Case Based Heuristically Accelerated Reinforcement Learning (CB-HARL), builds upon an emerging technique, the Heuristic Accelerated Reinforcement Learning (HARL), in which RL methods are accelerated by making use of heuristic information. CB-HARL is a subset of RL that makes use of a heuristic function derived from a case base, in a Case Based Reasoning manner. An algorithm that incorporates CBR techniques into the Heuristically Accelerated Q-Learning is also proposed. Empirical evaluations were conducted in a simulator for the RoboCup Four-Legged Soccer Competition, and results obtained shows that using CB-HARL, the agents learn faster than using either RL or HARL methods. © 2009 Springer Berlin Heidelberg.
dc.description.firstpage75
dc.description.lastpage89
dc.description.volume5650 LNAI
dc.identifier.citationBIANCHI, R.; ROS, R.; LOPES, DE M. R. Improving reinforcement learning by using case based heuristics. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). p. 75-89, July, 2009.
dc.identifier.doi10.1007/978-3-642-02998-1_7
dc.identifier.issn0302-9743
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/4281
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsAcesso Restrito
dc.titleImproving reinforcement learning by using case based heuristics
dc.typeArtigo de evento
fei.scopus.citations34
fei.scopus.eid2-s2.0-70350352555
fei.scopus.subjectCase base
fei.scopus.subjectCase based
fei.scopus.subjectCBr
fei.scopus.subjectEmpirical evaluations
fei.scopus.subjectHeuristic functions
fei.scopus.subjectHeuristic information
fei.scopus.subjectNew approaches
fei.scopus.subjectQ-learning
fei.scopus.subjectReinforcement learning techniques
fei.scopus.subjectRoboCup
fei.scopus.subjectSpeed-ups
fei.scopus.updated2024-07-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=70350352555&origin=inward
Arquivos
Coleções
Artigos