{"type":"ScholarlyArticle","title":"Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions","authors":[{"name":"Jihwan Jeong","slug":"jihwan-jeong","given":"Jihwan","family":"Jeong","affiliation":""},{"name":"Parth Jaggi","slug":"parth-jaggi","given":"Parth","family":"Jaggi","affiliation":""},{"name":"Scott Sanner","slug":"scott-sanner","given":"Scott","family":"Sanner","affiliation":""}],"abstract":"Recent advances in symbolic dynamic programming (SDP) have significantly broadened the class of MDPs for which exact closed-form value functions can be derived. However, no existing solution methods can solve complex discrete and continuous state MDPs where a linear program determines state transitions --- transitions that are often required in problems with underlying constrained flow dynamics arising in problems ranging from traffic signal control to telecommunications bandwidth planning. In this paper, we present a novel SDP solution method for MDPs with LP transitions and continuous piecewise linear dynamics by introducing a novel, fully symbolic argmax operator. On three diverse domains, we show the first automated exact closed-form SDP solution to these challenging problems and the significant advantages of our SDP approach over discretized approximations.","doi":"10.24963/ijcai.2021/562","url":"https://ijcai.org/proceedings/2021/562","pdf":"https://ijcai.org/proceedings/2021/0562.pdf","markdown":"https://ijcai.org/proceedings/2021/562.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/562","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Planning and Scheduling","track":"Main Track","number":562,"pages":{"first":4083,"last":4089},"keywords":["Uncertainty in AI: Markov Decision Processes","Planning and Scheduling: Planning under Uncertainty","Planning and Scheduling: Markov Decisions Processes"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}