{"type":"ScholarlyArticle","title":"C-Link: A Hierarchical Clustering Approach to Large-scale Near-optimal Coalition Formation","authors":[{"name":"Alessandro Farinelli","slug":"alessandro-farinelli","given":"Alessandro","family":"Farinelli","affiliation":""},{"name":"Manuele Bicego","slug":"manuele-bicego","given":"Manuele","family":"Bicego","affiliation":""},{"name":"Sarvapali D. Ramchurn","slug":"sarvapali-d-ramchurn","given":"Sarvapali D.","family":"Ramchurn","affiliation":""},{"name":"Mauro Zucchelli","slug":"mauro-zucchelli","given":"Mauro","family":"Zucchelli","affiliation":""}],"abstract":"Coalition formation is a fundamental approach to multi-agent coordination. In this paper we address the specific problem of coalition structure generation, and focus on providing good-enough solutions using a novel heuristic approach that is based on data clustering methods. In particular, we propose a hierarchical agglomerative clustering approach (C-Link), which uses a similarity criterion between coalitions based on the gain that the system achieves if two coalitions merge. We empirically evaluate C-Link on a synthetic benchmark data-set as well as in collective energy purchasing settings. Our results show that the C-link approach performs very well against an optimal benchmark based on Mixed-Integer Programming, achieving solutions which are in the worst case about 80% of the optimal (in the synthetic data-set), and 98% of the optimal (in the energy data-set). Thus we show that C-Link can return solutions for problems involving thousands of agents within minutes.","doi":null,"url":"https://ijcai.org/proceedings/2013/27","pdf":"https://ijcai.org/proceedings/2013/0027.pdf","markdown":"https://ijcai.org/proceedings/2013/27.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/27","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":27,"pages":{"first":106,"last":111},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}