Negotiation and cooperation in multi-agent environments
Artificial Intelligence - Special issue on economic principles of multi-agent systems
A coalition formation mechanism based on inter-agent trust relationships
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Dynamic Coalition Formation among Rational Agents
IEEE Intelligent Systems
Coalition formation in proportionally fair divisible auctions
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Qualitative reasoning model for tradeoff analysis
MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
An agent negotiation engine for collaborative decision making
MDAI'06 Proceedings of the Third international conference on Modeling Decisions for Artificial Intelligence
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In Group-Choice Decision Making (GCDM) where a number of stakeholders are involved in choosing a single solution from a set of available solution options, it is common for the stakeholders to form coalition during negotiation in order to increase their individual welfare. It is also common to use Multi-Agent Systems (MAS) to automate GCDM processes. In such MAS, agents have to form coalitions like their human counterparts, and within each coalition, the individual agents behave according to the strategies of their clients. This paper presents a coalition formation engine that has two coalition formation algorithms. One of the algorithms is based on the concept of static coalition formation, and the other is based on the concept of dynamic coalition formation. Moreover, the coalition formation engine is coupled with algorithms that govern the social behavior of the agents in their coalitions, to form an agent negotiation engine. Finally, this paper presents an example and simulation results that illustrate the operational effectiveness of the two coalition formation algorithms, as well as the algorithms that govern the social behavior of the agents.