{"language":[{"iso":"eng"}],"intvolume":"      2018","quality_controlled":"1","scopus_import":"1","title":"Computational approaches for stochastic shortest path on succinct MDPs","main_file_link":[{"url":"https://arxiv.org/abs/1804.08984","open_access":"1"}],"oa_version":"Preprint","day":"17","publisher":"IJCAI","year":"2018","ec_funded":1,"date_published":"2018-07-17T00:00:00Z","type":"conference","date_updated":"2024-03-25T23:30:19Z","volume":2018,"publication_identifier":{"isbn":["978-099924112-7"],"issn":["10450823"]},"isi":1,"related_material":{"record":[{"relation":"dissertation_contains","id":"8934","status":"public"}]},"_id":"5977","doi":"10.24963/ijcai.2018/653","conference":{"location":"Stockholm, Sweden","name":"IJCAI: International Joint Conference on Artificial Intelligence","end_date":"2018-07-19","start_date":"2018-07-13"},"author":[{"last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu","first_name":"Krishnendu","orcid":"0000-0002-4561-241X"},{"last_name":"Fu","id":"3AAD03D6-F248-11E8-B48F-1D18A9856A87","first_name":"Hongfei","full_name":"Fu, Hongfei"},{"orcid":"0000-0003-1702-6584","first_name":"Amir","full_name":"Goharshady, Amir","id":"391365CE-F248-11E8-B48F-1D18A9856A87","last_name":"Goharshady"},{"full_name":"Okati, Nastaran","first_name":"Nastaran","last_name":"Okati"}],"abstract":[{"text":"We consider the stochastic shortest path (SSP)problem for succinct Markov decision processes(MDPs), where the MDP consists of a set of vari-ables, and a set of nondeterministic rules that up-date the variables. First, we show that several ex-amples from the AI literature can be modeled assuccinct MDPs.  Then we present computationalapproaches for upper and lower bounds for theSSP problem: (a) for computing upper bounds, ourmethod is polynomial-time in the implicit descrip-tion of the MDP; (b) for lower bounds, we present apolynomial-time (in the size of the implicit descrip-tion) reduction to quadratic programming. Our ap-proach is applicable even to infinite-state MDPs.Finally, we present experimental results to demon-strate the effectiveness of our approach on severalclassical examples from the AI literature.","lang":"eng"}],"publication_status":"published","publication":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","department":[{"_id":"KrCh"}],"article_processing_charge":"No","month":"07","date_created":"2019-02-13T13:26:27Z","citation":{"short":"K. Chatterjee, H. Fu, A.K. Goharshady, N. Okati, in:, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI, 2018, pp. 4700–4707.","ama":"Chatterjee K, Fu H, Goharshady AK, Okati N. Computational approaches for stochastic shortest path on succinct MDPs. In: <i>Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence</i>. Vol 2018. IJCAI; 2018:4700-4707. doi:<a href=\"https://doi.org/10.24963/ijcai.2018/653\">10.24963/ijcai.2018/653</a>","mla":"Chatterjee, Krishnendu, et al. “Computational Approaches for Stochastic Shortest Path on Succinct MDPs.” <i>Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence</i>, vol. 2018, IJCAI, 2018, pp. 4700–07, doi:<a href=\"https://doi.org/10.24963/ijcai.2018/653\">10.24963/ijcai.2018/653</a>.","ieee":"K. Chatterjee, H. Fu, A. K. Goharshady, and N. Okati, “Computational approaches for stochastic shortest path on succinct MDPs,” in <i>Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence</i>, Stockholm, Sweden, 2018, vol. 2018, pp. 4700–4707.","chicago":"Chatterjee, Krishnendu, Hongfei Fu, Amir Kafshdar Goharshady, and Nastaran Okati. “Computational Approaches for Stochastic Shortest Path on Succinct MDPs.” In <i>Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence</i>, 2018:4700–4707. IJCAI, 2018. <a href=\"https://doi.org/10.24963/ijcai.2018/653\">https://doi.org/10.24963/ijcai.2018/653</a>.","ista":"Chatterjee K, Fu H, Goharshady AK, Okati N. 2018. Computational approaches for stochastic shortest path on succinct MDPs. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. IJCAI: International Joint Conference on Artificial Intelligence vol. 2018, 4700–4707.","apa":"Chatterjee, K., Fu, H., Goharshady, A. K., &#38; Okati, N. (2018). Computational approaches for stochastic shortest path on succinct MDPs. In <i>Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence</i> (Vol. 2018, pp. 4700–4707). Stockholm, Sweden: IJCAI. <a href=\"https://doi.org/10.24963/ijcai.2018/653\">https://doi.org/10.24963/ijcai.2018/653</a>"},"external_id":{"isi":["000764175404118"],"arxiv":["1804.08984"]},"project":[{"name":"Efficient Algorithms for Computer Aided Verification","grant_number":"ICT15-003","_id":"25892FC0-B435-11E9-9278-68D0E5697425"},{"name":"Rigorous Systems Engineering","call_identifier":"FWF","_id":"25832EC2-B435-11E9-9278-68D0E5697425","grant_number":"S 11407_N23"},{"call_identifier":"FP7","name":"Quantitative Graph Games: Theory and Applications","_id":"2581B60A-B435-11E9-9278-68D0E5697425","grant_number":"279307"}],"status":"public","page":"4700-4707","oa":1,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1"}