Vidal's library
Title: Multi-Dimensional, MultiStep Negotiation for Task Allocation in a Cooperative System
Author: Xiaoqin Zhang, Victor Lesser, and Rodion Podorozhny
Journal: Autonomous Agents and Multi-Agent Systems
Volume: 10
Number: 1
Pages: 5--40
Year: 2005
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.

Cited by 13  -  Google Scholar

@Article{zhang05b,
  author =	 {Xiaoqin Zhang and Victor Lesser and Rodion
                  Podorozhny},
  title =	 {Multi-Dimensional, MultiStep Negotiation for Task
                  Allocation in a Cooperative System},
  journal =	 {Autonomous Agents and Multi-Agent Systems},
  year =	 2005,
  volume =	 10,
  number =	 1,
  pages =	 {5--40},
  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.},
  keywords =     {multiagent negotiation distributed-search},
  url = 	 {http://jmvidal.cse.sc.edu/library/zhang05b.pdf},
  cluster = 	 {15429239047087695224}
}
Last modified: Wed Mar 9 10:16:28 EST 2011