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JAAMAS 2026

Multi-Dimensional, MultiStep Negotiation

Journal Article OriginalPaper Artificial Intelligence · Multi-Agent Systems

Abstract

Abstract We present a multi-dimensional, multi-step negotiation mechanism for task allocation among cooperative agents based on distributed search. This mechanism uses marginal utility gain and marginal utility cost to structure this search process, so as to find a solution that maximizes the agents’ combined utility. These two utility values together with temporal constraints summarize the agents’ local information and reduce the communication load. This mechanism is anytime in character: by investing more time, the agents increase the likelihood of getting a better solution. We also introduce a multiple attribute utility function into negotiations. This allows agents to negotiate over the multiple attributes of the commitment, which produces more options, making it more likely for agents to find a solution that increases the global utility. A set of protocols are constructed and the experimental result shows a phase transition phenomenon as the complexity of negotiation situation changes. A measure of negotiation complexity is developed that can be used by an agent to choose an appropriate protocol, allowing the agents to explicitly balance the gain from the negotiation and the resource usage of the negotiation.

Authors

Keywords

  • cooperative negotiation
  • distributed search
  • multi-agent system

Context

Venue
Autonomous Agents and Multi-Agent Systems
Archive span
2005-2026
Indexed papers
940
Paper id
768525784702441073