Multi-agent architecture for Multiaobjective optimization of Flexible Neural Tree

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@Article{Ammar:2016:Neurocomputing,
  author =       "Marwa Ammar and Souhir Bouaziz and Adel M. Alimi and 
                 Ajith Abraham",
  title =        "Multi-agent architecture for Multiaobjective
                 optimization of Flexible Neural Tree",
  journal =      "Neurocomputing",
  volume =       "214",
  pages =        "307--316",
  year =         "2016",
  ISSN =         "0925-2312",
  DOI =          "doi:10.1016/j.neucom.2016.06.019",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0925231216306579",
  abstract =     "In this paper, a multi-agent system is introduced to
                 parallelize the Flexible Beta Basis Function Neural
                 Network (FBBFNT)' training as a response to the time
                 cost challenge. Different agents are formed; a
                 Structure Agent is designed for the FBBFNT structure
                 optimization and a variable set of Parameter Agents is
                 used for the FBBFNT parameter optimization. The main
                 objectives of the FBBFNT learning process were the
                 accuracy and the structure complexity. With the
                 proposed multi-agent system, the main purpose is to
                 reach a good balance between these objectives. For
                 that, a multi-objective context was adopted which based
                 on Pareto dominance. The agents use two algorithms: the
                 Pareto dominance Extended Genetic Programming (PEGP)
                 and the Pareto Multi-Dimensional Particle Swarm
                 Optimization ( PMD _ PSO ) algorithms for the structure
                 and parameter optimization, respectively. The proposed
                 system is called Pareto Multi-Agent Flexible Neural
                 Tree ( PMA _ FNT ). To assess the effectiveness of PMA
                 _ FNT , four benchmark real datasets of classification
                 are tested. The results compared with some classifiers
                 published in the literature.",
  keywords =     "genetic algorithms, genetic programming, Flexible
                 Neural Tree, Multi-agent architecture, Multi-objective
                 optimization, Evolutionary Computation algorithms,
                 Negotiation, Classification",
}

Genetic Programming entries for Marwa Ammar Souhir Bouaziz Adel M Alimi Ajith Abraham

Citations