{"citation":{"ama":"Brázdil T, Brožek V, Chatterjee K, Forejt V, Kučera A. Markov decision processes with multiple long-run average objectives. Logical Methods in Computer Science. 2014;10(1). doi:10.2168/LMCS-10(1:13)2014","apa":"Brázdil, T., Brožek, V., Chatterjee, K., Forejt, V., & Kučera, A. (2014). Markov decision processes with multiple long-run average objectives. Logical Methods in Computer Science. International Federation of Computational Logic. https://doi.org/10.2168/LMCS-10(1:13)2014","short":"T. Brázdil, V. Brožek, K. Chatterjee, V. Forejt, A. Kučera, Logical Methods in Computer Science 10 (2014).","chicago":"Brázdil, Tomáš, Václav Brožek, Krishnendu Chatterjee, Vojtěch Forejt, and Antonín Kučera. “Markov Decision Processes with Multiple Long-Run Average Objectives.” Logical Methods in Computer Science. International Federation of Computational Logic, 2014. https://doi.org/10.2168/LMCS-10(1:13)2014.","mla":"Brázdil, Tomáš, et al. “Markov Decision Processes with Multiple Long-Run Average Objectives.” Logical Methods in Computer Science, vol. 10, no. 1, International Federation of Computational Logic, 2014, doi:10.2168/LMCS-10(1:13)2014.","ieee":"T. Brázdil, V. Brožek, K. Chatterjee, V. Forejt, and A. Kučera, “Markov decision processes with multiple long-run average objectives,” Logical Methods in Computer Science, vol. 10, no. 1. International Federation of Computational Logic, 2014.","ista":"Brázdil T, Brožek V, Chatterjee K, Forejt V, Kučera A. 2014. Markov decision processes with multiple long-run average objectives. Logical Methods in Computer Science. 10(1)."},"volume":10,"ddc":["000"],"date_created":"2018-12-11T11:56:29Z","department":[{"_id":"KrCh"}],"publication_status":"published","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","pubrep_id":"428","publication":"Logical Methods in Computer Science","month":"02","abstract":[{"text":"We study Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) functions. We consider two different objectives, namely, expectation and satisfaction objectives. Given an MDP with κ limit-average functions, in the expectation objective the goal is to maximize the expected limit-average value, and in the satisfaction objective the goal is to maximize the probability of runs such that the limit-average value stays above a given vector. We show that under the expectation objective, in contrast to the case of one limit-average function, both randomization and memory are necessary for strategies even for ε-approximation, and that finite-memory randomized strategies are sufficient for achieving Pareto optimal values. Under the satisfaction objective, in contrast to the case of one limit-average function, infinite memory is necessary for strategies achieving a specific value (i.e. randomized finite-memory strategies are not sufficient), whereas memoryless randomized strategies are sufficient for ε-approximation, for all ε > 0. We further prove that the decision problems for both expectation and satisfaction objectives can be solved in polynomial time and the trade-off curve (Pareto curve) can be ε-approximated in time polynomial in the size of the MDP and 1/ε, and exponential in the number of limit-average functions, for all ε > 0. Our analysis also reveals flaws in previous work for MDPs with multiple mean-payoff functions under the expectation objective, corrects the flaws, and allows us to obtain improved results.","lang":"eng"}],"date_published":"2014-02-14T00:00:00Z","license":"https://creativecommons.org/licenses/by/4.0/","title":"Markov decision processes with multiple long-run average objectives","intvolume":" 10","oa_version":"Published Version","oa":1,"date_updated":"2021-01-12T06:56:11Z","_id":"2234","has_accepted_license":"1","year":"2014","scopus_import":1,"project":[{"call_identifier":"FWF","grant_number":"P 23499-N23","_id":"2584A770-B435-11E9-9278-68D0E5697425","name":"Modern Graph Algorithmic Techniques in Formal Verification"},{"call_identifier":"FWF","grant_number":"S11407","_id":"25863FF4-B435-11E9-9278-68D0E5697425","name":"Game Theory"},{"grant_number":"279307","_id":"2581B60A-B435-11E9-9278-68D0E5697425","name":"Quantitative Graph Games: Theory and Applications","call_identifier":"FP7"},{"name":"Microsoft Research Faculty Fellowship","_id":"2587B514-B435-11E9-9278-68D0E5697425"}],"issue":"1","main_file_link":[{"url":"http://repository.ist.ac.at/id/eprint/428","open_access":"1"}],"doi":"10.2168/LMCS-10(1:13)2014","status":"public","ec_funded":1,"publisher":"International Federation of Computational Logic","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"publication_identifier":{"issn":["18605974"]},"day":"14","publist_id":"4727","language":[{"iso":"eng"}],"file_date_updated":"2020-07-14T12:45:34Z","author":[{"last_name":"Brázdil","full_name":"Brázdil, Tomáš","first_name":"Tomáš"},{"full_name":"Brožek, Václav","first_name":"Václav","last_name":"Brožek"},{"orcid":"0000-0002-4561-241X","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","last_name":"Chatterjee","full_name":"Chatterjee, Krishnendu","first_name":"Krishnendu"},{"full_name":"Forejt, Vojtěch","first_name":"Vojtěch","last_name":"Forejt"},{"full_name":"Kučera, Antonín","first_name":"Antonín","last_name":"Kučera"}],"file":[{"checksum":"803edcc2d8c1acfba44a9ec43a5eb9f0","file_id":"4656","date_created":"2018-12-12T10:07:57Z","content_type":"application/pdf","access_level":"open_access","date_updated":"2020-07-14T12:45:34Z","creator":"system","file_name":"IST-2016-428-v1+1_1104.3489.pdf","relation":"main_file","file_size":375388}],"quality_controlled":"1","type":"journal_article"}