Vidal's library
Title: The evolution and stability of cooperative traits
Author: Sandip Sen and Partha Sarathi Dutta
Book Tittle: Proceedings of the First Intenational Joint Conference on Autonomous Agents and Multiagent Systems
Pages: 1114-1120
Publisher: ACM Press, NY, NY
Year: 2002
Abstract: Recent works in multi-agent systems have identified agent behaviors that can develop and sustain mutually beneficial cooperative relationships with like-minded agents and can resist exploitation from sel sh agents. Researchers have proposed the use of a probabilistic reciprocity scheme that uses summary information from past interactions to decide whether or not to honor a request for help from another agent. This behavior has been found to be close to optimal in homogeneous groups and outperform exploiters in mixed groups. A major shortcoming of these experiments, however, is that the composition of the group in term of agent behaviors is fixed. We believe that real-life rational agents, on the contrary, will change their behaviors based on observed performances of different behavioral traits with the goal of maximizing performance.

Cited by 16  -  Google Scholar

@InProceedings{sen02a,
  author =	 {Sandip Sen and Partha Sarathi Dutta},
  title =	 {The evolution and stability of cooperative traits},
  booktitle =	 {Proceedings of the First Intenational Joint
                  Conference on Autonomous Agents and Multiagent
                  Systems},
  pages =	 {1114-1120},
  year =	 2002,
  publisher =	 {{ACM} Press, NY, NY},
  abstract =	 {Recent works in multi-agent systems have identified
                  agent behaviors that can develop and sustain
                  mutually beneficial cooperative relationships with
                  like-minded agents and can resist exploitation from
                  sel sh agents. Researchers have proposed the use of
                  a probabilistic reciprocity scheme that uses summary
                  information from past interactions to decide whether
                  or not to honor a request for help from another
                  agent. This behavior has been found to be close to
                  optimal in homogeneous groups and outperform
                  exploiters in mixed groups. A major shortcoming of
                  these experiments, however, is that the composition
                  of the group in term of agent behaviors is fixed. We
                  believe that real-life rational agents, on the
                  contrary, will change their behaviors based on
                  observed performances of different behavioral traits
                  with the goal of maximizing performance.},
  keywords =     {multiagent learning},
  url =		 {http://jmvidal.cse.sc.edu/library/sen02a.pdf},
  comment =	 {masrg},
  googleid = 	 {iRkdpqwTKGMJ:scholar.google.com/},
  cluster = 	 {7144982441065519497}
}
Last modified: Wed Mar 9 10:15:31 EST 2011