Coalition formation with uncertain heterogeneous information
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Fuzzy kernel-stable coalitions between rational agents
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
A robust deception-free coalition formation model
Proceedings of the 2004 ACM symposium on Applied computing
Coalition calculation in a dynamic agent environment
ICML '04 Proceedings of the twenty-first international conference on Machine learning
The Advantages of Compromising in Coalition Formation with Incomplete Information
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
A Two-Level Framework for Coalition Formation via Optimization and Agent Negotiation
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Learning How to Plan and Instantiate a Plan in Multi-Agent Coalition Formation
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Methods for task allocation via agent coalition formation
Artificial Intelligence
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Coalitions are often required for multi-agent collaboration. In this research, we consider tasks that can only be completed with the combined efforts of multiple agents using approaches which are both cooperative and competitive. Often agents forming coalitions determine optimal coalitions by looking at all possibilities. This requires an exponential algorithm and is not feasible when the number of agents and tasks is large. We propose agents use a two step process of first determining the task, and secondly, the agents that will be solicited to help complete the task. We describe polynomial time heuristics for each decision. We measure four different agent types using the described heuristics. We explore diminishing choices and performance under various parameters.