Analysis of emergent properties in a hybrid bio-inspired architecture for cognitive agents
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Ir a este contenido- Autor
- Año de publicación 2007
- Idioma Inglés
- Descripción
- In this work, a hybrid, self-configurable, multilayered and evolutio-nary architecture for cognitive agents is developed. Each layer of the subsump-tion 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 mechan-ism 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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Citación recomendada (normas APA)
- Oscar Javier; Antonio Jiménez Romero López, "Analysis of emergent properties in a hybrid bio-inspired architecture for cognitive agents", -:-, 2007. Consultado en línea en la Biblioteca Digital de Bogotá (https://www.bibliotecadigitaldebogota.gov.co/resources/2087672/), el día 2024-05-17.