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Yet, the general problem is undecidable, and policies require full (and thus potentially unbounded) traces of execution history. To provide good approximations of such policies, POMDP agents often employ randomization over action choices. We consider the problem of computing simpler policies for POMDPs, and provide several approaches to still ensure their expressiveness. Key aspects are (1) the combination of an arbitrary number of specifications the policies need to adhere to, (2) a restricted form of randomization, and (3) a light-weight preprocessing of the POMDP model to encode memory. We provide a novel encoding as a mixed-integer linear program as baseline to solve the underlying problems. Our experiments demonstrate that the policies we obtain are more robust, smaller, and easier to implement for an engineer than those obtained from state-of-the-art POMDP solvers.<\/jats:p>","DOI":"10.1007\/s10009-024-00747-0","type":"journal-article","created":{"date-parts":[[2024,6,9]],"date-time":"2024-06-09T20:02:01Z","timestamp":1717963321000},"page":"269-299","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Strong Simple Policies for POMDPs"],"prefix":"10.1007","volume":"26","author":[{"given":"Leonore","family":"Winterer","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ralf","family":"Wimmer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bernd","family":"Becker","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nils","family":"Jansen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,6,9]]},"reference":[{"key":"747_CR1","volume-title":"Constrained Markov Decision Processes","author":"E. 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