@incollection{yu2000social,
  abstract = {Trust is important wherever agents must interact. We consider the important case of interactions in electronic communities, where the agents assist and represent principal entities, such as people and businesses. We propose a social mechanism of reputation management, which aims at avoiding interaction with undesirable participants. Social mechanisms complement hard security techniques (such as passwords and digital certificates), which only guarantee that a party is authenticated and authorized, but do not ensure that it exercises its authorization in a way that is desirable to others. Social mechanisms are even more important when trusted third parties are not available. Our specific approach to reputation management leads to a decentralized society in which agents help each other weed out undesirable players.},
  address = {Berlin/Heidelberg},
  affiliation = {Department of Computer Science, North Carolina State University, Raleigh, NC 27695-7534, USA},
  author = {Yu, Bin and Singh, Munindar},
  booktitle = {Cooperative Information Agents IV - The Future of Information Agents in Cyberspace},
  doi = {10.1007/978-3-540-45012-2_15},
  editor = {Klusch, Matthias and Kerschberg, Larry},
  interhash = {1065a4963600ef4f9b4c034d3bbd9a50},
  intrahash = {337afcb67138b927b27a9687199e8568},
  isbn = {978-3-540-67703-1},
  keyword = {Computer Science},
  pages = {355--393},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {A Social Mechanism of Reputation Management in Electronic Communities},
  url = {http://dx.doi.org/10.1007/978-3-540-45012-2_15},
  volume = 1860,
  year = 2000
}

@inproceedings{yu2003searching,
  abstract = {A referral system is a multiagent system whose member agents are capable of giving and following referrals. The specific cases of interest arise where each agent has a user. The agents cooperate by giving and taking referrals so each can better help its user locate relevant information. This use of referrals mimics human interactions and can potentially lead to greater effectiveness and efficiency than in single-agent systems.Existing approaches consider what referrals may be given and treat the referring process simply as path search in a static graph. By contrast, the present approach understands referrals as arising in and influencing dynamic social networks, where the agents act autonomously based on local knowledge. This paper studies strategies using which agents may search dynamic social networks. It evaluates the proposed approach empirically for a community of AI scientists (partially derived from bibliographic data). Further, it presents a prototype system that assists users in finding other users in practical social networks.},
  acmid = {860587},
  address = {New York, NY, USA},
  author = {Yu, Bin and Singh, Munindar P.},
  booktitle = {Proceedings of the second international joint conference on Autonomous agents and multiagent systems},
  doi = {10.1145/860575.860587},
  interhash = {1d5f1932e29ea02f82948d4efd12a0ad},
  intrahash = {c6b422948459e04a86e766055608e55e},
  isbn = {1-58113-683-8},
  location = {Melbourne, Australia},
  numpages = {8},
  pages = {65--72},
  publisher = {ACM},
  title = {Searching social networks},
  url = {http://doi.acm.org/10.1145/860575.860587},
  year = 2003
}