Methods for task allocation via agent coalition formation
Artificial Intelligence
Coalition structure generation with worst case guarantees
Artificial Intelligence
Agent memory and adaptation in multi-agent systems
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Coalition Formation for Large-Scale Electronic Markets
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
A column generation approach to the coalition formation problem in multi-agent systems
Computers and Operations Research
On the computational complexity of qualitative coalitional games
Artificial Intelligence
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In this paper, we present a rigorous analysis of an agent-based coalition formation mechanism in emarkets proposed by Lerman and Shehory. While the agent-based coalition formation shows good performance through simulations, our analysis provides guidelines for agent designers to simplify the system design. We show that the coalition formations with different initial distributions converge to a unique steady state. The steady state, which represents both the final coalition distribution and the global utility gain, is proven to be determined by buyer agents' local strategies. The global utility gain is shown to increase as the number of buyer agents increases. In a system of uniform-attachment-uniform-detachment rates, the global utility gain is proven to increase as the detachment rate decreases.