Abstract
The knowledge about higher brain centres in insects and how they affect the insect’s behaviour has increased significantly in recent years by experimental investigations. A large body of evidence suggests that higher brain centres of insects are important for learning, short-term and long-term memory and play an important role for context generalisation. In this paper, we focus on artificial recurrent neural networks that model non-linear systems, in particular, Lotka-Volterra systems. After studying the typical behavior and processes that emerge in appropiate Lotka-Volterra systems, we analyze the relationship between sequential memory encoding processes and the higher brain centres in insects in order to propose a way to develop a general ’insect-brain’ control architecture to be implemented on simple robots.
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Bedia, M.G., Corchado, J.M., Castillo, L.F. (2007). Bio-inspired Memory Generation by Recurrent Neural Networks. In: Sandoval, F., Prieto, A., Cabestany, J., Graña, M. (eds) Computational and Ambient Intelligence. IWANN 2007. Lecture Notes in Computer Science, vol 4507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73007-1_8
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DOI: https://doi.org/10.1007/978-3-540-73007-1_8
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