Hidden order: how adaptation builds complexity
Hidden order: how adaptation builds complexity
Communications of the ACM
Evolving social rationality for MAS using "tags"
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
The Knowledge Engineering Review
A survey of trust and reputation systems for online service provision
Decision Support Systems
Effective tag mechanisms for evolving coordination
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Applying a socially inspired technique (tags) to improve cooperation in P2P networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Changing neighbours: improving tag-based cooperation
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Norm diversity and emergence in tag-based cooperation
COIN@AAMAS'10 Proceedings of the 6th international conference on Coordination, organizations, institutions, and norms in agent systems
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Establishing and maintaining cooperation is an enduring problem in multi-agent systems and, although several solutions exist, the increased use of online trading systems, peer-to-peer networks, and ubiquitous computing environments mean that it remains an important question. Environments are emerging in which large numbers of agents are required to cooperate, but where repeat interactions between agents may be rare or non-existent. Most existing approaches to cooperation rely on reciprocity to establish notions of trust and reputation. However, where repeat interactions are rare such approaches are not always effective. In this paper we use ideas from biology and the social sciences to provide a mechanism that supports cooperation in such environments. Our mechanism combines a tag-based method to enable co-operation given a lack of reciprocity, with an adaptation of a simple image scoring reputation model to cope with cheating agents. Using a simple peer-to-peer scenario we show how cooperative behaviour is favoured, and how the influence of cheating agents can be reduced using only minimal information about an agent's neighbours.