Kiefer, Stefan, Mayr, Richard, Shirmohammadi, Mahsa, Totzke, Patrick 
ORCID: 0000-0001-5274-8190 and Wojtczak, Dominik ORCID: 0000-0001-5560-0546
(2020)
How to Play in Infinite MDPs (Invited Talk).
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Abstract
Markov decision processes (MDPs) are a standard model for dynamic systems that exhibit both stochastic and nondeterministic behavior. For MDPs with finite state space it is known that for a wide range of objectives there exist optimal strategies that are memoryless and deterministic. In contrast, if the state space is infinite, optimal strategies may not exist, and optimal or ε-optimal strategies may require (possibly infinite) memory. In this paper we consider qualitative objectives: reachability, safety, (co-)Büchi, and other parity objectives. We aim at giving an introduction to a collection of techniques that allow for the construction of strategies with little or no memory in countably infinite MDPs.
| Item Type: | Conference or Workshop Item (Unspecified) |
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| Additional Information: | urn: urn:nbn:de:0030-drops-124103 |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 28 Aug 2020 09:12 |
| Last Modified: | 18 Jan 2023 23:36 |
| DOI: | 10.4230/LIPIcs.ICALP.2020.3 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3098914 |
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