Vidal's library
Title: Helping based on future expectations
Author: Sabyasachi Saha, Sandip Sen, and Partha Sarathi Dutta
Book Tittle: Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Pages: 289--296
Publisher: ACM Press, New York, NY.
Year: 2003
DOI: 10.1145/860575.860622
Abstract: Autonomous agents interacting in an open world can be considered to be primarily driven by self interests. Previous work in this area has prescribed a strategy of reciprocal behavior, based on past interactions, for promoting and sustaining cooperation among such self-interested agents. Here we present a new mechanism where agents base their decisions both on historical data as well as on future interaction expectations. A decision mechanism is presented that compares current helping cost with expected future savings from interaction with the agent requesting help. We experiment with heterogeneous agents that have varying expertise for di...

Cited by 13  -  Google Scholar

@inproceedings{saha03a,
  author =	 {Sabyasachi Saha and Sandip Sen and Partha Sarathi
                  Dutta},
  title =	 {Helping based on future expectations},
  googleid =	 {bxFK4XkSeKIJ:scholar.google.com/},
  booktitle =	 {Proceedings of the second international joint
                  conference on Autonomous agents and multiagent
                  systems},
  year =	 2003,
  pages =	 {289--296},
  location =	 {Melbourne, Australia},
  doi =		 {10.1145/860575.860622},
  publisher =	 {ACM Press, New York, NY.},
  abstract =	 {Autonomous agents interacting in an open world can
                  be considered to be primarily driven by self
                  interests. Previous work in this area has prescribed
                  a strategy of reciprocal behavior, based on past
                  interactions, for promoting and sustaining
                  cooperation among such self-interested agents. Here
                  we present a new mechanism where agents base their
                  decisions both on historical data as well as on
                  future interaction expectations. A decision
                  mechanism is presented that compares current helping
                  cost with expected future savings from interaction
                  with the agent requesting help. We experiment with
                  heterogeneous agents that have varying expertise for
                  di...},
  keywords =     {multiagent learning game-theory},
  url =		 {http://jmvidal.cse.sc.edu/library/saha03a.pdf},
  comment =	 {masrg},
  cluster = 	 {11707127546029674863},
}
Last modified: Wed Mar 9 10:15:49 EST 2011