Bio-inspired cognitive architecture for adaptive agents based on an evolutionary approach
Manifestación
- Autores
- Identificador
- 870153
- Fecha de publicación
- 2008
- Forma obra
- Texto
- Lugar de producción
- 2008
- Idioma
- inglés
- Nota de edición
- Digitalización realizada por la Biblioteca Virtual del Banco de la República (Colombia)
- Materias
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- Tecnología; Tecnología / Ingeniería y operaciones afines
- Notas
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- Colfuturo
- © Derechos reservados del autor
- Artificial immune systems; Cognitive science.; Connectionist Q-Learning; Extended classifier systems; gene Expression programming; Hybrid behaviour Co-evolution; Subsumption architecture
- 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 Reinforcement Machine Learning System (RMLS) based on bio-inspired techniques.
In this research an evolutionary mechanism based 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 too. The proposed approach was tested in an animat environment (artificial life) using a multi-agent platform and it exhibited several learning capabilities and emergent properties for self-configuring internal agent’s architecture.
- Enlace permanente
- https://www.cervantesvirtual.com/obra/bio-inspired-cognitive-architecture-for-adaptive-agents-based-on-an-evolutionary-approach-870153
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