Evolving Cooperation Strategies
Technical Report, UTULSA-MCS-94-10. The University of Tulsa, Tulsa, OK, USA, (16 December 1994)Zusammenfassung
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.