{"type":"ScholarlyArticle","title":"Scalable Multiagent Planning Using Probabilistic Inference","authors":[{"name":"Akshat Kumar","slug":"akshat-kumar","given":"Akshat","family":"Kumar","affiliation":""},{"name":"Shlomo Zilberstein","slug":"shlomo-zilberstein","given":"Shlomo","family":"Zilberstein","affiliation":""},{"name":"Marc Toussaint","slug":"marc-toussaint","given":"Marc","family":"Toussaint","affiliation":""}],"abstract":"Multiagent planning has seen much progress with the development of formal models such as Dec-POMDPs. However, the complexity of these models—NEXP-Complete even for two agents—has limited scalability. We identify certain mild conditions that are sufficient to make multiagent planning amenable to a scalable approximation w.r.t. the number of agents. This is achieved by constructing a graphical model in which likelihood maximization is equivalent to plan optimization. Using the Expectation-Maximization framework for likelihood maximization, we show that the necessary inference can be decomposed into processes that often involve a small subset of agents, thereby facilitating scalability. We derive a global update rule that combines these local inferences to monotonically increase the overall solution quality. Experiments on a large multiagent planning benchmark confirm the benefits of the new approach in terms of runtime and scalability.","doi":"10.5591/978-1-57735-516-8/IJCAI11-357","url":"https://ijcai.org/proceedings/2011/357","pdf":"https://ijcai.org/proceedings/2011/0357.pdf","markdown":"https://ijcai.org/proceedings/2011/357.md","bibtex":"https://ijcai.org/proceedings/2011/bibtex/357","volume":{"slug":"2011","title":"Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2011","url":"https://ijcai.org/proceedings/2011/","year":2011,"location":"Barcelona, Catalonia, Spain","dates":"16–22 July 2011","editors":"Toby Walsh","isbn":"978-1-57735-512-0; 978-1-57735-513-7; 978-1-57735-514-4; 978-1-57735-515-1; 978-1-57735-516-8","publisher":"AAAI Press/International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":357,"pages":{"first":2140,"last":2145},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}