{"date_published":"2022-02-01T00:00:00Z","department":[{"_id":"GradSch"},{"_id":"KrCh"}],"date_updated":"2025-04-15T06:29:59Z","article_type":"original","scopus_import":"1","project":[{"name":"Game Theory","_id":"25863FF4-B435-11E9-9278-68D0E5697425","grant_number":"S11407","call_identifier":"FWF"}],"year":"2022","intvolume":"        47","acknowledgement":"Partially supported by Austrian Science Fund (FWF) NFN Grant No RiSE/SHiNE S11407, by CONICYT Chile through grant PII 20150140, and by ECOS-CONICYT through grant C15E03.\r\n","doi":"10.1287/moor.2020.1116","month":"02","date_created":"2021-04-08T09:33:31Z","volume":47,"page":"100-119","isi":1,"oa":1,"author":[{"last_name":"Chatterjee","full_name":"Chatterjee, Krishnendu","orcid":"0000-0002-4561-241X","first_name":"Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87"},{"id":"BD1DF4C4-D767-11E9-B658-BC13E6697425","full_name":"Saona Urmeneta, Raimundo J","first_name":"Raimundo J","orcid":"0000-0001-5103-038X","last_name":"Saona Urmeneta"},{"full_name":"Ziliotto, Bruno","first_name":"Bruno","last_name":"Ziliotto"}],"publisher":"Institute for Operations Research and the Management Sciences","oa_version":"Preprint","external_id":{"isi":["000731918100001"],"arxiv":["1904.13360"]},"abstract":[{"text":"Partially observable Markov decision processes (POMDPs) are standard models for dynamic systems with probabilistic and nondeterministic behaviour in uncertain environments. We prove that in POMDPs with long-run average objective, the decision maker has approximately optimal strategies with finite memory. This implies notably that approximating the long-run value is recursively enumerable, as well as a weak continuity property of the value with respect to the transition function. ","lang":"eng"}],"article_processing_charge":"No","keyword":["Management Science and Operations Research","General Mathematics","Computer Science Applications"],"publication":"Mathematics of Operations Research","arxiv":1,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","issue":"1","language":[{"iso":"eng"}],"citation":{"apa":"Chatterjee, K., Saona Urmeneta, R. J., &#38; Ziliotto, B. (2022). Finite-memory strategies in POMDPs with long-run average objectives. <i>Mathematics of Operations Research</i>. Institute for Operations Research and the Management Sciences. <a href=\"https://doi.org/10.1287/moor.2020.1116\">https://doi.org/10.1287/moor.2020.1116</a>","short":"K. Chatterjee, R.J. Saona Urmeneta, B. Ziliotto, Mathematics of Operations Research 47 (2022) 100–119.","ista":"Chatterjee K, Saona Urmeneta RJ, Ziliotto B. 2022. Finite-memory strategies in POMDPs with long-run average objectives. Mathematics of Operations Research. 47(1), 100–119.","mla":"Chatterjee, Krishnendu, et al. “Finite-Memory Strategies in POMDPs with Long-Run Average Objectives.” <i>Mathematics of Operations Research</i>, vol. 47, no. 1, Institute for Operations Research and the Management Sciences, 2022, pp. 100–19, doi:<a href=\"https://doi.org/10.1287/moor.2020.1116\">10.1287/moor.2020.1116</a>.","ama":"Chatterjee K, Saona Urmeneta RJ, Ziliotto B. Finite-memory strategies in POMDPs with long-run average objectives. <i>Mathematics of Operations Research</i>. 2022;47(1):100-119. doi:<a href=\"https://doi.org/10.1287/moor.2020.1116\">10.1287/moor.2020.1116</a>","chicago":"Chatterjee, Krishnendu, Raimundo J Saona Urmeneta, and Bruno Ziliotto. “Finite-Memory Strategies in POMDPs with Long-Run Average Objectives.” <i>Mathematics of Operations Research</i>. Institute for Operations Research and the Management Sciences, 2022. <a href=\"https://doi.org/10.1287/moor.2020.1116\">https://doi.org/10.1287/moor.2020.1116</a>.","ieee":"K. Chatterjee, R. J. Saona Urmeneta, and B. Ziliotto, “Finite-memory strategies in POMDPs with long-run average objectives,” <i>Mathematics of Operations Research</i>, vol. 47, no. 1. Institute for Operations Research and the Management Sciences, pp. 100–119, 2022."},"publication_status":"published","_id":"9311","type":"journal_article","quality_controlled":"1","publication_identifier":{"issn":["0364-765X"],"eissn":["1526-5471"]},"main_file_link":[{"url":"https://arxiv.org/abs/1904.13360","open_access":"1"}],"title":"Finite-memory strategies in POMDPs with long-run average objectives","status":"public","day":"01"}