{"conference":{"location":"London, United Kingdom","start_date":"2015-04-11","end_date":"2015-04-18","name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems"},"citation":{"ista":"Brázdil T, Chatterjee K, Forejt V, Kučera A. 2015. Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives. 9035, 181–187.","mla":"Brázdil, Tomáš, et al. Multigain: A Controller Synthesis Tool for MDPs with Multiple Mean-Payoff Objectives. Vol. 9035, Springer, 2015, pp. 181–87, doi:10.1007/978-3-662-46681-0_12.","short":"T. Brázdil, K. Chatterjee, V. Forejt, A. Kučera, 9035 (2015) 181–187.","apa":"Brázdil, T., Chatterjee, K., Forejt, V., & Kučera, A. (2015). Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives. Presented at the TACAS: Tools and Algorithms for the Construction and Analysis of Systems, London, United Kingdom: Springer. https://doi.org/10.1007/978-3-662-46681-0_12","chicago":"Brázdil, Tomáš, Krishnendu Chatterjee, Vojtěch Forejt, and Antonín Kučera. “Multigain: A Controller Synthesis Tool for MDPs with Multiple Mean-Payoff Objectives.” Lecture Notes in Computer Science. Springer, 2015. https://doi.org/10.1007/978-3-662-46681-0_12.","ieee":"T. Brázdil, K. Chatterjee, V. Forejt, and A. Kučera, “Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives,” vol. 9035. Springer, pp. 181–187, 2015.","ama":"Brázdil T, Chatterjee K, Forejt V, Kučera A. Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives. 2015;9035:181-187. doi:10.1007/978-3-662-46681-0_12"},"doi":"10.1007/978-3-662-46681-0_12","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"abstract":[{"text":"We present MultiGain, a tool to synthesize strategies for Markov decision processes (MDPs) with multiple mean-payoff objectives. Our models are described in PRISM, and our tool uses the existing interface and simulator of PRISM. Our tool extends PRISM by adding novel algorithms for multiple mean-payoff objectives, and also provides features such as (i) generating strategies and exploring them for simulation, and checking them with respect to other properties; and (ii) generating an approximate Pareto curve for two mean-payoff objectives. In addition, we present a new practical algorithm for the analysis of MDPs with multiple mean-payoff objectives under memoryless strategies.","lang":"eng"}],"publist_id":"5263","publisher":"Springer","alternative_title":["LNCS"],"quality_controlled":"1","main_file_link":[{"url":"http://arxiv.org/abs/1501.03093","open_access":"1"}],"project":[{"grant_number":"P 23499-N23","_id":"2584A770-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Modern Graph Algorithmic Techniques in Formal Verification"},{"grant_number":"S 11407_N23","name":"Rigorous Systems Engineering","call_identifier":"FWF","_id":"25832EC2-B435-11E9-9278-68D0E5697425"},{"grant_number":"279307","call_identifier":"FP7","_id":"2581B60A-B435-11E9-9278-68D0E5697425","name":"Quantitative Graph Games: Theory and Applications"}],"series_title":"Lecture Notes in Computer Science","date_published":"2015-01-01T00:00:00Z","day":"01","ec_funded":1,"status":"public","publication_status":"published","oa_version":"Preprint","oa":1,"intvolume":" 9035","month":"01","date_updated":"2020-01-21T13:18:52Z","page":"181 - 187","volume":9035,"date_created":"2018-12-11T11:54:18Z","department":[{"_id":"KrCh"}],"_id":"1839","title":"Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives","author":[{"last_name":"Brázdil","full_name":"Brázdil, Tomáš","first_name":"Tomáš"},{"orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu"},{"full_name":"Forejt, Vojtěch","last_name":"Forejt","first_name":"Vojtěch"},{"last_name":"Kučera","full_name":"Kučera, Antonín","first_name":"Antonín"}],"type":"conference","year":"2015"}