Vidal's libraryTitle: | 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