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Innovations in Hybrid Intelligent Systems pp 1–8Cite as

Analysis of Emergent Properties in a Hybrid Bio-inspired Architecture for Cognitive Agents

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Part of the book series: Advances in Soft Computing ((AINSC,volume 44))

Abstract

In this work, a hybrid, self-configurable, multilayered and evolutionary architecture for cognitive agents is developed. Each layer of the subsumption architecture is modeled by one different Machine Learning System MLS based on bio-inspired techniques. In this research an evolutionary mechanism supported on Gene Expression Programming 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.

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Author information

Authors and Affiliations

  1. LSIIS Department, Politécnica de Madrid University, Boadilla del monte, 28660, Madrid, Spain

    Oscar J. Romero & Angélica de Antonio

Authors
  1. Oscar J. Romero
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  2. Angélica de Antonio
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Editor information

Editors and Affiliations

  1. Escuela Politécnica Superior Campus Vena, Edifico C, Universidad de Burgos, C/Francisco de Vitoria s/n, 09006, Burgos, Spain

    Emilio Corchado

  2. Departamento de Informática y Automática Facultad de Ciencias, Universidad de Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Juan M. Corchado

  3. Centre for Quantifiable Quality of Service in Communication Systems (Q2S) Centre of Excellence, Norwegian University of Science and Technology, O.S. Bragstads plass 2E, 7491, Trondheim, Norway

    Ajith Abraham

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© 2007 Springer-Verlag Berlin Heidelberg

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Romero, O.J., de Antonio, A. (2007). Analysis of Emergent Properties in a Hybrid Bio-inspired Architecture for Cognitive Agents. In: Corchado, E., Corchado, J.M., Abraham, A. (eds) Innovations in Hybrid Intelligent Systems. Advances in Soft Computing, vol 44. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74972-1_2

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  • DOI: https://doi.org/10.1007/978-3-540-74972-1_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74971-4

  • Online ISBN: 978-3-540-74972-1

  • eBook Packages: EngineeringEngineering (R0)

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