• Media type: Electronic Conference Proceeding; E-Article; Text
  • Title: Strategies for MDP Bisimilarity Equivalence and Inequivalence
  • Contributor: Kiefer, Stefan [Author]; Tang, Qiyi [Author]
  • imprint: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2022
  • Language: English
  • DOI: https://doi.org/10.4230/LIPIcs.CONCUR.2022.32
  • Keywords: Markov decision processes ; Markov chains
  • Origination:
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  • Description: A labelled Markov decision process (MDP) is a labelled Markov chain with nondeterminism; i.e., together with a strategy a labelled MDP induces a labelled Markov chain. Motivated by applications to the verification of probabilistic noninterference in security, we study problems whether there exist strategies such that the labelled MDPs become bisimilarity equivalent/inequivalent. We show that the equivalence problem is decidable; in fact, it is EXPTIME-complete and becomes NP-complete if one of the MDPs is a Markov chain. Concerning the inequivalence problem, we show that (1) it is decidable in polynomial time; (2) if there are strategies for inequivalence then there are memoryless strategies for inequivalence; (3) such memoryless strategies can be computed in polynomial time.
  • Access State: Open Access