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  • 标题:Strategy Complexity of Parity Objectives in Countable MDPs
  • 本地全文:下载
  • 作者:Stefan Kiefer ; Richard Mayr ; Mahsa Shirmohammadi
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2020
  • 卷号:171
  • 页码:39:1-39:17
  • DOI:10.4230/LIPIcs.CONCUR.2020.39
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:We study countably infinite MDPs with parity objectives. Unlike in finite MDPs, optimal strategies need not exist, and may require infinite memory if they do. We provide a complete picture of the exact strategy complexity of ε-optimal strategies (and optimal strategies, where they exist) for all subclasses of parity objectives in the Mostowski hierarchy. Either MD-strategies, Markov strategies, or 1-bit Markov strategies are necessary and sufficient, depending on the number of colors, the branching degree of the MDP, and whether one considers ε-optimal or optimal strategies. In particular, 1-bit Markov strategies are necessary and sufficient for ε-optimal (resp. optimal) strategies for general parity objectives.
  • 关键词:Markov decision processes; Parity objectives; Levy’s zero-one law
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