Multiagent Negotiation on Multiple Issues with Incomplete Information

We present a reactive offer generation method for general multiagent multi-attribute negotiation, where the agents have non-linear utility functions and no information about the utility functions of other agents. We prove the convergence of the proposing method and characterize the convergence rate under a finite negotiation time. We also prove that rational agents do not have any incentive to deviate from the proposed strategy. We further present simulation results to demonstrate that on randomly generated problem instances the solution obtained from our protocol is quite close to the Nash bargaining solution.

Authors

• Ronghuo Zheng Carnegie Mellon University
• Nilanjan Chakraborty Carnegie Mellon University
• Tinglong Dai Carnegie Mellon University, USA
• Katia Sycara Carnegie Mellon University

Keywords

• Multiagent Negotiation
• Incomplete Information
• Convergence