Multilayered Evolutionary Architecture for Behaviour Arbitration in Cognitive Agents

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Romero-Lopez:EL,
  author =       "Oscar Javier Romero Lopez",
  title =        "Multilayered Evolutionary Architecture for Behaviour
                 Arbitration in Cognitive Agents",
  journal =      "Engineering Letters",
  year =         "2007",
  volume =       "15",
  number =       "2",
  pages =        "193--202",
  publisher =    "International Association of Engineers",
  keywords =     "genetic algorithms, genetic programming, Gene
                 Expression Programming, Hybrid Behaviour Co-evolution,
                 Subsumption Architecture",
  ISSN =         "1816-0948",
  URL =          "http://www.engineeringletters.com/issues_v15/issue_2/EL_15_2_04.pdf",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.148.6014",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  language =     "en",
  oai =          "oai:CiteSeerXPSU:10.1.1.148.6014",
  abstract =     "--- In this work, an hybrid, self-configurable,
                 multilayered and evolutionary subsumption architecture
                 for cognitive agents is developed. Each layer of the
                 multilayered architecture is modeled by one different
                 Machine Learning System (MLS) based on bio-inspired
                 techniques such as Extended Classifier Systems (XCS),
                 Artificial Immune Systems (AIS), Neuro Connectionist
                 Q-Learning (NQL) and Learning Classifier Systems (LCS)
                 among others. In this research an evolutionary
                 mechanism based on gene expression programming (GEP) to
                 self-configure the behaviour arbitration between layers
                 is suggested. In addition, a co-evolutionary mechanism
                 to evolve behaviours in an independent and parallel
                 fashion is used. The proposed approach was tested in an
                 animat environment using a multi-agent platform and it
                 exhibited several learning capabilities and emergent
                 properties for self-configuring internal agent{'}s
                 architecture.",
  notes =        "http://www.engineeringletters.com/",
}

Genetic Programming entries for Oscar Javier Romero Lopez

Citations