Evolving Cooperation Strategies   [CS]

by

Haynes, T., Wainwright, R. and Sen, S.

Literature search on Evolutionary ComputationBBase ©1999-2013, Rasmus K. Ursem
     Home · Search · Adv. search · Authors · Login · Add entries   Webmaster
Note to authors: Please submit your bibliography and contact information - online papers are more frequently cited.

Info: 1994
Keywords:genetic algorithms, genetic programming, ccoperation strategies
Abstract:
The identification, design, and implementation of strategies for cooperation is a central research issue in the field of Distributed Artificial Intelligence [AI] (DAI). We propose a novel approach to the construction of cooperation strategies [CS] for a group of problem solvers based on the Genetic Programming (GP) paradigm. [GP] GP's are a class of adaptive algorithms used to evolve solution structures that optimize a given evaluation criterion. Our approach is based on designing a representation for cooperation strategies [CS] that can be manipulated by GPs. We present results from experiments in the predator-prey domain, which has been extensively studied as an easy-to-describe but difficult-to-solve cooperation problem domain. They key aspect of our approach is the minimal reliance on domain knowledge and human intervention in the construction of good cooperation strategies. [CS] Promising comparison results with prior systems lend credence to the viability of this approach.
Notes:
URL(s):Postscript
(G)zipped postscript

Review item:

Mark as doublet (will be reviewed)

Print entry




BibTex:
@TechReport{Hayes:1994:ecs,
  author =       "Thomas Haynes and Roger Wainwright and Sandip Sen",
  title =        "Evolving Cooperation Strategies",
  institution =  "The University of Tulsa",
  year =         "1994",
  type =         "Technical Report",
  number =       "UTULSA-MCS-94-10",
  address =      "Tulsa, OK, USA",
  month =        "16 " # dec,
  keywords =     "genetic algorithms, genetic programming, ccoperation
                 strategies",
  URL =          "http://euler.mcs.utulsa.edu/~haynes/icmas95.ps",
  abstract =     "The identification, design, and implementation of
                 strategies for cooperation is a central research issue
                 in the field of Distributed Artificial Intelligence
                 (DAI). We propose a novel approach to the construction
                 of cooperation strategies for a group of problem
                 solvers based on the Genetic Programming (GP) paradigm.
                 GP's are a class of adaptive algorithms used to evolve
                 solution structures that optimize a given evaluation
                 criterion. Our approach is based on designing a
                 representation for cooperation strategies that can be
                 manipulated by GPs. We present results from experiments
                 in the predator-prey domain, which has been extensively
                 studied as an easy-to-describe but difficult-to-solve
                 cooperation problem domain. They key aspect of our
                 approach is the minimal reliance on domain knowledge
                 and human intervention in the construction of good
                 cooperation strategies. Promising comparison results
                 with prior systems lend credence to the viability of
                 this approach.",
  size =         "9 pages",
  notes =        "

                 ",
}