[{"OA_type":"green","oa_version":"Preprint","date_created":"2026-04-12T22:01:50Z","volume":40,"abstract":[{"text":"Robust Markov Decision Processes (RMDPs) generalize classical MDPs that consider uncertainties in transition probabilities by defining a set of possible transition functions. An objective is a set of runs (or infinite trajectories) of the RMDP, and the value for an objective is the maximal probability that the agent can guarantee against the adversarial environment. We consider (a) reachability objectives, where given a target set of states, the goal is to eventually arrive at one of them; and (b) parity objectives, which are a canonical representation for ω-regular objectives. The qualitative analysis problem asks whether the objective can be ensured with probability 1. In this work, we study the qualitative problem for reachability and parity objectives on RMDPs without making any assumption over the structures of the RMDPs, e.g., unichain or aperiodic. Our contributions are twofold. We first present efficient algorithms with oracle access to uncertainty sets that solve qualitative problems of reachability and parity objectives. We then report experimental results demonstrating the effectiveness of our oracle-based approach on classical RMDP examples from the literature scaling up to thousands of states.","lang":"eng"}],"scopus_import":"1","external_id":{"arxiv":["2505.04539"]},"intvolume":"        40","issue":"43","oa":1,"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2505.04539"}],"publication_status":"published","status":"public","doi":"10.1609/aaai.v40i43.40931","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"KrCh"},{"_id":"GradSch"}],"day":"14","project":[{"name":"Formal Methods for Stochastic Models: Algorithms and Applications","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818","call_identifier":"H2020"}],"arxiv":1,"ec_funded":1,"title":"Qualitative analysis of ω-regular objectives on robust MDPs","author":[{"full_name":"Asadi, Ali","id":"02d96aae-000e-11ec-b801-cadd0a5eefbb","first_name":"Ali","last_name":"Asadi"},{"full_name":"Chatterjee, Krishnendu","first_name":"Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","last_name":"Chatterjee","orcid":"0000-0002-4561-241X"},{"first_name":"Ehsan","id":"103b4fa0-896a-11ed-bdf8-87b697bef40d","last_name":"Kafshdar Goharshadi","full_name":"Kafshdar Goharshadi, Ehsan","orcid":"0000-0002-8595-0587"},{"last_name":"Karrabi","id":"67638922-f394-11eb-9cf6-f20423e08757","first_name":"Mehrdad","full_name":"Karrabi, Mehrdad","orcid":"0009-0007-5253-9170"},{"last_name":"Shafiee","id":"2783031a-7378-11f0-b2d0-f17f1db2ebad","first_name":"Ali","full_name":"Shafiee, Ali"}],"date_published":"2026-03-14T00:00:00Z","type":"conference","publication":"Proceedings of the 40th AAAI Conference on Artificial Intelligence","article_processing_charge":"No","publication_identifier":{"eissn":["2374-3468"],"issn":["2159-5399"]},"quality_controlled":"1","OA_place":"repository","acknowledgement":"This work was supported by ERC CoG 863818 (ForMSMArt) and Austrian Science Fund (FWF) 10.55776/COE12. We also thank Hossein Zakerinia for his helpful feedback.","conference":{"end_date":"2026-01-27","start_date":"2026-01-20","location":"Singapore, Singapore","name":"AAAI: Conference on Artificial Intelligence"},"year":"2026","publisher":"Association for the Advancement of Artificial Intelligence","language":[{"iso":"eng"}],"month":"03","_id":"21717","citation":{"apa":"Asadi, A., Chatterjee, K., Goharshady, E., Karrabi, M., &#38; Shafiee, A. (2026). Qualitative analysis of ω-regular objectives on robust MDPs. In <i>Proceedings of the 40th AAAI Conference on Artificial Intelligence</i> (Vol. 40, pp. 36137–36145). Singapore, Singapore: Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v40i43.40931\">https://doi.org/10.1609/aaai.v40i43.40931</a>","short":"A. Asadi, K. Chatterjee, E. Goharshady, M. Karrabi, A. Shafiee, in:, Proceedings of the 40th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2026, pp. 36137–36145.","ista":"Asadi A, Chatterjee K, Goharshady E, Karrabi M, Shafiee A. 2026. Qualitative analysis of ω-regular objectives on robust MDPs. Proceedings of the 40th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 40, 36137–36145.","mla":"Asadi, Ali, et al. “Qualitative Analysis of ω-Regular Objectives on Robust MDPs.” <i>Proceedings of the 40th AAAI Conference on Artificial Intelligence</i>, vol. 40, no. 43, Association for the Advancement of Artificial Intelligence, 2026, pp. 36137–45, doi:<a href=\"https://doi.org/10.1609/aaai.v40i43.40931\">10.1609/aaai.v40i43.40931</a>.","ama":"Asadi A, Chatterjee K, Goharshady E, Karrabi M, Shafiee A. Qualitative analysis of ω-regular objectives on robust MDPs. In: <i>Proceedings of the 40th AAAI Conference on Artificial Intelligence</i>. Vol 40. Association for the Advancement of Artificial Intelligence; 2026:36137-36145. doi:<a href=\"https://doi.org/10.1609/aaai.v40i43.40931\">10.1609/aaai.v40i43.40931</a>","ieee":"A. Asadi, K. Chatterjee, E. Goharshady, M. Karrabi, and A. Shafiee, “Qualitative analysis of ω-regular objectives on robust MDPs,” in <i>Proceedings of the 40th AAAI Conference on Artificial Intelligence</i>, Singapore, Singapore, 2026, vol. 40, no. 43, pp. 36137–36145.","chicago":"Asadi, Ali, Krishnendu Chatterjee, Ehsan Goharshady, Mehrdad Karrabi, and Ali Shafiee. “Qualitative Analysis of ω-Regular Objectives on Robust MDPs.” In <i>Proceedings of the 40th AAAI Conference on Artificial Intelligence</i>, 40:36137–45. Association for the Advancement of Artificial Intelligence, 2026. <a href=\"https://doi.org/10.1609/aaai.v40i43.40931\">https://doi.org/10.1609/aaai.v40i43.40931</a>."},"date_updated":"2026-05-04T11:38:56Z","page":"36137-36145"}]