An evolutionary game-theoretical approach to particle swarm optimisation

Authors:
Cecilia Di Chio;Paolo Di Chio;Mario Giacobini
Affiliations:
Department of Computer Science, University of Essex, UK;Dipartimento di Sistemi e Istituzioni per l'Economia, University of L'Aquila, Italy;Department of Animal Production, Epidemiology and Ecology and Molecular Biotechnology Center, University of Torino, Italy
Venue:
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Year:
2008

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Abstract

This work merges ideas from two very different areas: Particle Swarm Optimisation and Evolutionary Game Theory. In particular, we are looking to integrate strategies from the Prisoner Dilemma, namely cooperate and defect, into the Particle Swarm Optimisation algorithm. These strategies represent different methods to evaluate each particle's next position. At each iteration, a particle chooses to use one or the other strategy according to the outcome at the previous iteration (variation in its fitness). We compare some variations of the newly introduced algorithm with the standard Particle Swarm Optimiser on five benchmark problems.