Coalition formation with uncertain heterogeneous information
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Multi-agent Coalition via Autonomous Price Negotiation in a Real-Time Web Environment
IAT '03 Proceedings of the IEEE/WIC International Conference on Intelligent Agent Technology
Task Allocation via Multi-Agent Coalition Formation: Taxonomy, Algorithms and Complexity
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
Forming efficient agent groups for completing complex tasks
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Methods for task allocation via agent coalition formation
Artificial Intelligence
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In this paper we analyze and propose solutions for complex tasks allocation problem that have predetermined and known overall payments for any given task. More specifically, here we concentrated on scenarios where agents are willing to undertake any subtask of their capabilities but can strategize on their cost reported for completing this subtask. For this environment we proved that no individually rational and budget balanced protocol can exist which archives an efficient solution. Moreover, there are settings in this environment for which such protocols exist, but they are again setting specific. Given this we then go onto develop protocol for important class of settings, that we prove to be budget balanced, individually rational and is incentive compatible in Bayesian Nash equilibrium. Moreover, although it does not achieve the efficient allocation solution, we show by experiments that for the majority of cases a near optimal (above 95%) solution is achieved.