Abstract
Recently, brain models attempt to support cognitive abilities of artificial organisms. Incremental approaches are often employed to support modelling process. The present work introduces a novel computational framework for incremental brain modelling, which aims at enforcing partial components re-usability. A coevolutionary agent-based approach is followed which utilizes properly formulated neural agents to represent brain areas. A collaborative coevolutionary method, with the inherent ability to design cooperative substructures, supports the implementation of partial brain models, and additionally supplies a consistent method to achieve their integration. The implemented models are embedded in a robotic platform to support its behavioral capabilities.
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References
Compte, A., Brunel, N., Goldman-Rakic, P.S., Wang, X.-J.: Synaptic mechanisms and network dynamics underlying spatial working memory in a cortical network model. Cerebral Cortex 10(1), 910–923 (2000)
Cotterill, R.M.J.: Cooperation of the basal ganglia, cerebellum, sensory cerebrum and hippocampus: possible implications for cognition, consciousness, intelligence and creativity. Progress in Neurobiology 64(1), 1–33 (2001)
Floreano, D., Urzelai, J.: Evolutionary robots with on-line self-organization and behavioral fitness. Neural Networks 13, 431–443 (2000)
Fuster, J.M.: Executive frontal functions. Experimental Brain Research 133, 66–70 (2000)
Kandel, E.R., Schwartz, J.H., Jessell, T.M.: Principles of Neural Science. Mc Graw Hill, New York (2000)
Maniadakis, M., Trahanias, P.: Evolution tunes coevolution: modelling robot cognition mechanisms. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol. 3102, pp. 640–641. Springer, Heidelberg (2004)
Maniadakis, M., Trahanias, P.: A Hierarchical Coevolutionary Method to Support Brain-Lesion Modelling. In: Proc. of Int. Joint Conference on Neural Networks, IJCNN 2005 (2005)
Maniadakis, M., Trahanias, P.: Modelling Brain Emergent Behaviors Through Coevolution of Neural Agents., Neural Networks journal (accepted for publication)
Metta, G., Panerai, F., Manzotti, R., Sandini, G.: Babybot: an artificial developing robotic agent. In: Proc. of SAB 2000 (2000)
Moriarty, D.E., Miikkulainen, R.: Forming Neural Networks Through Efficient and Adaptive Coevolution. Evolutionary Computation 5(4), 373–399 (1997)
Poter, M., De Jong, K.: Cooperative coevolution: An architecture for evolving coadapted subcomponents. Evolutionary Computation 8, 1–29 (2000)
Ragozzino, M.E., Kesner, R.P.: The role of rat dorsomedial prefrontal cortex in working memory for egocentric responces. Neuroscience Letters 308, 145–148 (2001)
Reilly, R.G., Marian, I.: Cortical Software Re-Use: A Computational Principle for Cognitive Development in Robots. In: Proc. ICDL 2002 (2002)
Rolls, E.T., Stringer, S.M.: On the design of neural networks in the brain by genetic evolution. Progress in Neurobiology 61, 557–579 (2000)
Scassellati, B.: Theory of Mind for a Humanoid Robot. Autonomous Robots 12(1), 13–24 (2002)
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Maniadakis, M., Trahanias, P. (2005). CoEvolutionary Incremental Modelling of Robotic Cognitive Mechanisms. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds) Advances in Artificial Life. ECAL 2005. Lecture Notes in Computer Science(), vol 3630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553090_21
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DOI: https://doi.org/10.1007/11553090_21
Publisher Name: Springer, Berlin, Heidelberg
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