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

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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
DOIs
StatePublished - 1 Jun 2020

Funding

FundersFunder number
NSFC-ISF2510/17
European Cooperation in Science and Technology
Israel Science Foundation217/17, 722/18

    Keywords

    • Markov decision process
    • Overtaking optimality
    • Perron–Frobenius eigenvalue
    • Reachability objective
    • Safety objective

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