Reference : A Multi-Agent Organizational Framework for Coevolutionary Optimization
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/16742
A Multi-Agent Organizational Framework for Coevolutionary Optimization
English
Danoy, Grégoire mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Bouvry, Pascal mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Boissier, Olivier [ENSM.SE, G2I/SMA, Saint-Etienne, France]
2010
Lecture Notes in Computer Science
Springer
4
199-224
Yes
0302-9743
1611-3349
[en] Multi-Agent Systems ; Organizational Model ; Evolutionary Algorithms
[en] 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.
http://hdl.handle.net/10993/16742
10.1007/978-3-642-18222-8_9
http://www.springerlink.com/content/t81676856q6j4n4x/

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