Controlling cooperative problem solving in industrial multi-agent systems using joint intentions
Artificial Intelligence
Compromise in negotiation: exploiting worth functions over states
Artificial Intelligence
Representations and solutions for game-theoretic problems
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Modeling agents as qualitative decision makers
Artificial Intelligence - Special issue on economic principles of multi-agent systems
On stable social laws and qualitative equilibria
Artificial Intelligence
Game theoretic reasoning in multi-agent coordination by negotiation with a trusted third party
Proceedings of the third annual conference on Autonomous Agents
A Fuzzy Game Theoretic Approach to Multi-Agent Coordination
PRIMA '98 Selected papers from the First Pacific Rim International Workshop on Multi-Agents, Multiagent Platforms
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
Mechanisms for automated negotiation in state oriented domains
Journal of Artificial Intelligence Research
Negotiation and task sharing among autonomous agents in cooperative domains
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Risk control in multi-agent coordination by negotiation with a trusted third party
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Equilibrium analysis of the possibilities of unenforced exchange in multiagent systems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Methods for task allocation via agent coalition formation
Artificial Intelligence
Advantages of a leveled commitment contracting protocol
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Agent Negotiation under Uncertainty and Risk
PRIMA '00 Proceedings of the Third Pacific Rim International Workshop on Multi-Agents: Design and Applications of Intelligent Agents
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The optimal decision for an agent in a given game situation depends on the decisions of other agents at the same time. Rational agents will find a stable equilibrium before taking an action, according to the assumption of rationality. We suggest that the rational agents can use the negotiation mechanism to reach the equilibrium. In previous works, we proposed the communication actions of guarantee and compensation to convince or persuade other agents with a trusted third party mediating the games. In this paper, we extend the negotiation mechanism to deal with n-by-n games and justify its optimality with the underlying assumptions. During the negotiation process, each agent makes suggestions on how they can reach equilibrium while maximizing its own payoff. The mechanism can deal with all the game situations and find an acceptable equilibrium that gives optimal payoffs for the agents.