{"type":"ScholarlyArticle","title":"Probabilistic Inference Based Message-Passing for Resource Constrained DCOPs","authors":[{"name":"Supriyo Ghosh","slug":"supriyo-ghosh","given":"Supriyo","family":"Ghosh","affiliation":""},{"name":"Akshat Kumar","slug":"akshat-kumar","given":"Akshat","family":"Kumar","affiliation":""},{"name":"Pradeep Varakantham","slug":"pradeep-varakantham","given":"Pradeep","family":"Varakantham","affiliation":""}],"abstract":"Distributed constraint optimization (DCOP) is an important framework for coordinated multiagent decision making. We address a practically useful variant of DCOP, called resource-constrained DCOP (RC-DCOP), which takes into account agents' consumption of shared limited resources. We present a promising new class of algorithm for RC-DCOPs by translating the underlying coordination problem to probabilistic inference. Using inference techniques such as expectation-maximization and convex optimization machinery, we develop a novel convergent message-passing algorithm for RC-DCOPs. Experiments on standard benchmarks show that our approach provides better quality than previous best DCOP algorithms and has much lower failure rate. Comparisons against an efficient centralized solver show that our approach provides near-optimal solutions, and is significantly faster on larger instances.","doi":null,"url":"https://ijcai.org/proceedings/2015/64","pdf":"https://ijcai.org/proceedings/2015/0064.pdf","markdown":"https://ijcai.org/proceedings/2015/64.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/64","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Distributed Search/CSP/Optimization","track":"Main Track","number":64,"pages":{"first":411,"last":416},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}