Reachability and Safety Objectives in Markov Decision Processes on Long but Finite Horizons

Galit Ashkenazi-Golan, Janos Flesch*, Arkadi Predtetchinski, Eilon Solan

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

We consider discrete-time Markov decision processes in which the decision maker is interested in long but finite horizons. First we consider reachability objective: the decision maker's goal is to reach a specific target state with the highest possible probability. A strategy is said to overtake another strategy, if it gives a strictly higher probability of reaching the target state on all sufficiently large but finite horizons. We prove that there exists a pure stationary strategy that is not overtaken by any pure strategy nor by any stationary strategy, under some condition on the transition structure and respectively under genericity. A strategy that is not overtaken by any other strategy, called an overtaking optimal strategy, does not always exist. We provide sufficient conditions for its existence. Next we consider safety objective: the decision maker's goal is to avoid a specific state with the highest possible probability. We argue that the results proven for reachability objective extend to this model.
Original languageEnglish
Pages (from-to)945-965
Number of pages21
JournalJournal of Optimization Theory and Applications
Volume185
Issue number3
Early online date18 May 2020
DOIs
Publication statusPublished - Jun 2020

Keywords

  • Markov decision process
  • Reachability objective
  • Safety objective
  • Overtaking optimality
  • Perron-Frobenius eigenvalue
  • OPTIMALITY
  • OVERTAKING

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