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

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@InProceedings{Romero2007,

• author = "Oscar J. Romero and Angelica {de Antonio}",
• title = "Analysis of Emergent Properties in a Hybrid Bio-inspired Architecture for Cognitive Agents",
• booktitle = "Innovations in Hybrid Intelligent Systems",
• year = "2007",
• editor = "Emilio Corchado and Juan M. Corchado and Ajith Abraham",
• volume = "44",
• series = "Advances in Soft Computing",
• pages = "1--8",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, Gene Expression Programming, Subsumption Architecture, Hybrid Behaviour, Co-evolution, Artificial Immune Systems, Extended Classifier Systems, Neuro Connectionist, Q-Learning Systems",
• isbn13 = "978-3-540-74972-1",
• URL = "https://doi.org/10.1007/978-3-540-74972-1_2",
• DOI = "doi:10.1007/978-3-540-74972-1_2",
• abstract = "In this work, a hybrid, self-configurable, multilayered and evolutionary architecture for cognitive agents is developed. Each layer of the subsumption architecture is modelled 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 architecture.",

}

Genetic Programming entries for Oscar Javier Romero Lopez Angelica de Antonio Jimenez

Citations