The evolution and stability of cooperative traits
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Agent teaching agent framework
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Effect of referrals on convergence to satisficing distributions
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Reciprocal resource sharing in P2P environments
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Predicting agent strategy mix of evolving populations
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Effect of joining decisions on peer clusters
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Distributed intrusion detection in partially observable Markov decision processes
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Multi-dimensional bid improvement algorithm for simultaneous auctions
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
An efficient protocol for negotiation over multiple indivisible resources
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Emergence of norms through social learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
The impact of recommender systems on item-, user-, and rating-diversity
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
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We believe that intelligent information agents will represent their users interest in electronic marketplaces and other forums to trade, exchange, share, identify, and locate goods and services. Such information worlds will present unforeseen opportunities as well as challenges that can be best addressed by robust, self-sustaining agent communities. An agent community is a stable, adaptive group of self-interested agents that share common resources and must coordinate their efforts to effectively develop, utilize and nurture group resources and organization. More specifically, agents will need mechanisms to benefit from complementary expertise in the group, pool together resources to meet new demands and exploit transient opportunities, negotiate fair settlements, develop norms to facilitate coordination, exchange help and transfer knowledge between peers, secure the community against intruders, and learn to collaborate effectively. In this talk, I will summarize some of our research results on trust-based computing, negotiation, and learning that will enable intelligent agents to develop and sustain robust, adaptive, and successful agent communities.