A multi-agent method for forming and dynamic restructuring of pareto optimal coalitions
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
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
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
Coalition Formation Strategies for Self-Interested Agents
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
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In coalition formation, often the utility associated with completion of a task changes over time. One common class of environments discounts utility in each time. We develop a strategy for decision making in the so called shrinking pie environment. We focus on compromising techniques and explore three different acceptance policies. Through our testing, we determine that agents must be willing to compromise and consider the discount in order to maximize their own utility and the overall efficiency of the system.