{"type":"ScholarlyArticle","title":"A Reputation Management Approach for Resource Constrained Trustee Agents","authors":[{"name":"Han Yu","slug":"han-yu","given":"Han","family":"Yu","affiliation":"Nanyang Technological University , Singapore"},{"name":"Chunyan Miao","slug":"chunyan-miao","given":"Chunyan","family":"Miao","affiliation":"Nanyang Technological University , Singapore"},{"name":"Bo An","slug":"bo-an","given":"Bo","family":"An","affiliation":"The Key Lab of Intelligent Information Processing , Institute of Computing Technology , Chinese Academy of Sciences , China"},{"name":"Cyril Leung","slug":"cyril-leung","given":"Cyril","family":"Leung","affiliation":"University of British Columbia , Canada"},{"name":"Victor R. Lesser","slug":"victor-r-lesser","given":"Victor R.","family":"Lesser","affiliation":"University of Massachusetts Amherst , USA"}],"abstract":"Trust is an important mechanism enabling agents to self-police open and dynamic multi-agent systems (ODMASs). Trusters evaluate the reputation of trustees based on their past observed performance, and use this information to guide their future interaction decisions. Existing trust models tend to concentrate trusters' interactions on a small number of highly reputable trustees to minimize risk exposure. When a trustee's servicing capacity is limited, such an approach may cause long delays for trusters and subsequently damage the reputation of trustees. To mitigate this problem, we propose a reputation management approach for trustee agents based on distributed constraint optimization. It helps a trustee to make situation-aware decisions on which incoming requests to serve and prevent the resulting reputation score from being affected by factors out of the trustee's control. The approach is evaluated through theoretical analysis and within a simulated, highly dynamic multi-agent environment. The results show that it can achieve close to optimally efficient utilization of the trustee agents' collective capacity in an ODMAS, promotes fair treatment of trustee agents based on their behavior, and significantly outperforms related work in enhancing social welfare.","doi":null,"url":"https://ijcai.org/proceedings/2013/69","pdf":"https://ijcai.org/proceedings/2013/0069.pdf","markdown":"https://ijcai.org/proceedings/2013/69.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/69","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":69,"pages":{"first":418,"last":423},"keywords":[],"videos":[],"references":[{"position":1,"raw":"[Ipeirotis, 2010] Panagiotis G. 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