{"type":"ScholarlyArticle","title":"Event-Detecting Multi-Agent MDPs: Complexity and Constant-Factor Approximations","authors":[{"name":"Akshat Kumar","slug":"akshat-kumar","given":"Akshat","family":"Kumar","affiliation":""},{"name":"Shlomo Zilberstein","slug":"shlomo-zilberstein","given":"Shlomo","family":"Zilberstein","affiliation":""}],"abstract":"Planning under uncertainty for multiple agents has flourished with the development of formal models such as multi-agent MDPs and decentralized MDPs. Despite their richness, applicability of these models remains limited due to their computational complexity. We present the class of event-detecting Multi-agent MDPs (eMMDPs), designed to detect multiple mobile targets by a team of sensor agents. We show that eMMDPs are NP-Hard and present a scalable 2-approximation algorithm for solving them using matroid theory and constraint optimization. Its complexity is linear in the state-space and number of agents, quadratic in the horizon, and exponential only in a small parameter that depends on the interaction among the agents. Despite the worst-case approximation ratio of 2, experimental results show that the algorithm produces nearoptimal policies for a range of test problems.Akshat Kumar, Shlomo Zilberstein","doi":null,"url":"https://ijcai.org/proceedings/2009/43","pdf":"https://ijcai.org/proceedings/2009/0043.pdf","markdown":"https://ijcai.org/proceedings/2009/43.md","bibtex":"https://ijcai.org/proceedings/2009/bibtex/43","volume":{"slug":"2009","title":"Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2009","url":"https://ijcai.org/proceedings/2009/","year":2009,"location":"Pasadena, California, USA","dates":"","editors":"Hiroaki Kitano","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":43,"pages":{"first":201,"last":206},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}