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Une Approche Multi Agent Pour Les Algorithmes Genetiques Coevolutionnaires Hybrides Et Dynamiques
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Book Synopsis Une Approche Multi-agent Pour Les Algorithmes Génétiques Coévolutionnaires Hybrides Et Dynamiques by : Grégoire Danoy
Download or read book Une Approche Multi-agent Pour Les Algorithmes Génétiques Coévolutionnaires Hybrides Et Dynamiques written by Grégoire Danoy and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation we assert that modeling Coevolutionary Genetic Algorithms (CGAs) as organizational multi-agent systems overcomes the lack of explicitness at the level of the algorithms structure, interactions and adaptation to existing models and platforms. We therefore introduce MAS4EVO, Multi-Agent Systems for EVolutionary Optimization, a new agent (re-)organizational model based on Moise+ and dedicated to evolutionary optimization. This model was used to describe existing CGAs as well as to build two new variants, hybrid and dynamic, of a competitive CGA. MAS4EVO is implemented in DAFO (Distributed Agent Framework for Optimization) which permits the use, the manipulation and the distribution of these CGAs, on hard optimization problems. The CGAs experimentations were conducted on two business problems, the first one being an inventory management problem and the second one being a new topology control problem in wireless ad hoc networks.
Book Synopsis Une Approche Multi-agent Pour Les Algorithmes Génétiques Coévolutionnaires Hybrides Et Dynamiques by : Grégoire Danoy
Download or read book Une Approche Multi-agent Pour Les Algorithmes Génétiques Coévolutionnaires Hybrides Et Dynamiques written by Grégoire Danoy and published by . This book was released on 2008 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation we assert that modeling Coevolutionary Genetic Algorithms (CGAs) as organizational multi-agent systems overcomes the lack of explicitness at the level of the algorithms structure, interactions and adaptation to existing models and platforms. We therefore introduce MAS4EVO, Multi-Agent Systems for EVolutionary Optimization, a new agent (re-)organizational model based on Moise+ and dedicated to evolutionary optimization. This model was used to describe existing CGAs as well as to build two new variants, hybrid and dynamic, of a competitive CGA. MAS4EVO is implemented in DAFO (Distributed Agent Framework for Optimization) which permits the use, the manipulation and the distribution of these CGAs, on hard optimization problems. The CGAs experimentations were conducted on two business problems, the first one being an inventory management problem and the second one being a new topology control problem in wireless ad hoc networks.
