Answer set programming for non-stationary Markov decision processes

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dc.contributor.authorFerreira L.A.
dc.contributor.authorC. Bianchi R.A.
dc.contributor.authorSantos P.E.
dc.contributor.authorde Mantaras R.L.
dc.date.accessioned2019-08-19T23:45:19Z
dc.date.available2019-08-19T23:45:19Z
dc.date.issued2017
dc.description.abstract© 2017, Springer Science+Business Media New York.Non-stationary domains, where unforeseen changes happen, present a challenge for agents to find an optimal policy for a sequential decision making problem. This work investigates a solution to this problem that combines Markov Decision Processes (MDP) and Reinforcement Learning (RL) with Answer Set Programming (ASP) in a method we call ASP(RL). In this method, Answer Set Programming is used to find the possible trajectories of an MDP, from where Reinforcement Learning is applied to learn the optimal policy of the problem. Results show that ASP(RL) is capable of efficiently finding the optimal solution of an MDP representing non-stationary domains.
dc.description.firstpage993
dc.description.issuenumber4
dc.description.lastpage1007
dc.description.volume47
dc.identifier.citationAnjoletto, L.; Bianchi; Santos, Paulo; De MANTARAS, R. L.. Answer Set Programming for Non-Stationary Markov Decision Processes. APPLIED INTELLIGENCE, v. 1, p. 1, 2017.
dc.identifier.doi10.1007/s10489-017-0988-y
dc.identifier.issn1573-7497
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/1210
dc.relation.ispartofApplied Intelligence
dc.rightsAcesso Restrito
dc.subject.otherlanguageAction languages
dc.subject.otherlanguageAnswer set programming
dc.subject.otherlanguageMarkov decision processes
dc.subject.otherlanguageNon-determinism
dc.titleAnswer set programming for non-stationary Markov decision processes
dc.typeArtigo
fei.scopus.citations10
fei.scopus.eid2-s2.0-85025441238
fei.scopus.subjectAction language
fei.scopus.subjectAnswer set programming
fei.scopus.subjectMarkov Decision Processes
fei.scopus.subjectNon Determinism
fei.scopus.subjectNonstationary
fei.scopus.subjectOptimal policies
fei.scopus.subjectOptimal solutions
fei.scopus.subjectSequential decision making
fei.scopus.updated2024-03-04
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85025441238&origin=inward
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