Methods for task allocation via agent coalition formation
Artificial Intelligence
Coalition formation with uncertain heterogeneous information
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Distributed Sensor Networks: A Multiagent Perspective
Distributed Sensor Networks: A Multiagent Perspective
Brain Meets Brawn: Why Grid and Agents Need Each Other
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
On Safe Kernel Stable Coalition Forming among Agents
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Bayesian Reinforcement Learning for Coalition Formation under Uncertainty
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
The Knowledge Engineering Review
Engineering distributed protocols for multi-agent interactions using game theory
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Agent long-term coalition credit
Expert Systems with Applications: An International Journal
Using coalitions of wind generators and electric vehicles for effective energy market participation
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Sequentially optimal repeated coalition formation under uncertainty
Autonomous Agents and Multi-Agent Systems
BSCA-P: privacy preserving coalition formation
MATES'05 Proceedings of the Third German conference on Multiagent System Technologies
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We define Trusted Kernel-based Coalition Formation as a novel extension to the traditional kernel-based coalition formation process which ensures agents choose the most reliable coalition partners and are guaranteed to obtain the payment they deserve. To this end, we develop an encryption-based communication protocol and a payment scheme which ensure that agents cannot manipulate the mechanism to their own benefit. Moreover, we integrate a generic trust model in the coalition formation process that permits the selection of the most reliable agents over repeated coalition games. We empirically evaluate our mechanism when iterated and show that, in the long run, it always chooses the coalition structure that has the maximum expected value and determines the payoffs that match their level of reliability.