Emerging Properties of Knowledge Sharing Referral Networks: Considerations of Effectiveness and Fairness
Referral-based peer-to-peer networks have a wide range of applications. They provide a natural framework in which agents can help each other. This paper studies the trade-off between social welfare and fairness in referral networks. The traditional, naive mechanism yields high social welfare but at the cost of some agents—in particular, the “best” ones—being exploited. Autonomous agents would obviously not participate in such networks. An obvious mechanism such as reciprocity improves fairness but substantially lowers welfare. A more general incentive mechanism yields high fairness with only a small loss in welfare. This paper considers substructures of the network that emerge and cause the above outcomes.
KeywordsSocial Welfare Relative Performance MultiAgent System Autonomous Agent Agent Exploitation
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- 5.Sen, S.: Reciprocity: a foundational principle for promoting cooperative behavior among self-interested agents. In: Proceedings of the 2nd International Conference on Multiagent Systems, pp. 322–329. AAAI Press, Menlo Park (1996)Google Scholar
- 6.Hales, D., Edmonds, B.: Evolving social rationality for MAS using ”tags”. In: Proceedings of the 2nd International Joint Conference on Autonomous Agents and MultiAgent Systems (AAMAS). ACM Press (2003) (to appear)Google Scholar
- 7.Yu, B., Singh, M.P.: Incentive mechanisms for peer-to-peer systems. In: Proceedings of the 2nd International Workshop on Agents and Peer-to-Peer Computing (2003)Google Scholar
- 8.Krishnan, R., Smith, M.D., Telang, R.: The economics of peer-to-peer networks. Working paper, Carnegie Mellon University (2002)Google Scholar
- 9.Golle, P., Leyton-Brown, K., Mironov, I.: Incentives for sharing in peer-to-peer networks. In: Proceedings of the 3rd International Conference on Electronic Commerce (EC), pp. 264–267 (2001)Google Scholar