Multilayered Evolutionary Architecture for Behaviour Arbitration in Cognitive Agents

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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