Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language pBC+

Yi Wang, Joohyung Lee

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

Abstract

We extend probabilistic action language pBC+ with the notion of utility in decision theory. The semantics of the extended pBC+ can be defined as a shorthand notation for a decision-theoretic extension of the probabilistic answer set programming language LPMLN. Alternatively, the semantics of pBC+ can also be defined in terms of Markov Decision Process (MDP), which in turn allows for representing MDP in a succinct and elaboration tolerant way as well as leveraging an MDP solver to compute a pBC+ action description. The idea led to the design of the system pbcplus2mdp, which can find an optimal policy of a pBC+ action description using an MDP solver.

Original languageEnglish (US)
Title of host publicationLogic Programming and Nonmonotonic Reasoning - 15th International Conference, LPNMR 2019, Proceedings
EditorsYuliya Lierler, Stefan Woltran, Marcello Balduccini
PublisherSpringer Verlag
Pages224-238
Number of pages15
ISBN (Print)9783030205270
DOIs
StatePublished - Jan 1 2019
Event15th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2019 - Philadelphia, United States
Duration: Jun 3 2019Jun 7 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11481 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2019
CountryUnited States
CityPhiladelphia
Period6/3/196/7/19

Fingerprint

Markov Decision Process
Semantics
Decision theory
Computer programming languages
Probabilistic Programming
Answer Set Programming
Decision Theory
Optimal Policy
Notation
Programming Languages
Language

Keywords

  • Action language
  • Answer set programming
  • Markov Decision Process

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Wang, Y., & Lee, J. (2019). Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language pBC+. In Y. Lierler, S. Woltran, & M. Balduccini (Eds.), Logic Programming and Nonmonotonic Reasoning - 15th International Conference, LPNMR 2019, Proceedings (pp. 224-238). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11481 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-20528-7_17

Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language pBC+. / Wang, Yi; Lee, Joohyung.

Logic Programming and Nonmonotonic Reasoning - 15th International Conference, LPNMR 2019, Proceedings. ed. / Yuliya Lierler; Stefan Woltran; Marcello Balduccini. Springer Verlag, 2019. p. 224-238 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11481 LNAI).

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

Wang, Y & Lee, J 2019, Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language pBC+. in Y Lierler, S Woltran & M Balduccini (eds), Logic Programming and Nonmonotonic Reasoning - 15th International Conference, LPNMR 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11481 LNAI, Springer Verlag, pp. 224-238, 15th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2019, Philadelphia, United States, 6/3/19. https://doi.org/10.1007/978-3-030-20528-7_17
Wang Y, Lee J. Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language pBC+. In Lierler Y, Woltran S, Balduccini M, editors, Logic Programming and Nonmonotonic Reasoning - 15th International Conference, LPNMR 2019, Proceedings. Springer Verlag. 2019. p. 224-238. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-20528-7_17
Wang, Yi ; Lee, Joohyung. / Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language pBC+. Logic Programming and Nonmonotonic Reasoning - 15th International Conference, LPNMR 2019, Proceedings. editor / Yuliya Lierler ; Stefan Woltran ; Marcello Balduccini. Springer Verlag, 2019. pp. 224-238 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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