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A Multi-Agent Organizational Framework for Coevolutionary Optimization

Abstract : This paper introduces DAFO, a Distributed Agent Framework for Optimization that helps in designing and applying Coevolutionary Genetic Algorithms (CGAs). CGAs have already proven to be efficient in solving hard optimization problems, however they have not been considered in the existing agent-based metaheuristics frameworks that currently provide limited organization models. As a solution, DAFO includes a complete organization and reorganization model, Multi-Agent System for EVolutionary Optimization (MAS4EVO), that permits to formalize CGAs structure, interactions and adaptation. Examples of existing and original CGAs modeled using MAS4EVO are provided and an experimental proof of their efficiency is given on an emergent topology control problem in mobile hybrid ad hoc networks called the injection network problem.
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Contributor : Florent Breuil Connect in order to contact the contributor
Submitted on : Friday, November 18, 2011 - 4:20:35 PM
Last modification on : Wednesday, June 24, 2020 - 4:19:08 PM

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Gregoire Danoy, Pascal Bouvry, Olivier Boissier. A Multi-Agent Organizational Framework for Coevolutionary Optimization. Jensen, Kurt; Donatelli, Susanna; Koutny, Maciej. Transactions on Petri Nets and Other Models of Concurrency IV, Springer Berlin / Heidelberg, pp.199-224, 2010, Lecture Notes in Computer Science, ⟨10.1007/978-3-642-18222-8_9⟩. ⟨emse-00642758⟩



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