Abstract
Swimming for the lamprey (an eel-like fish) is governed by activity in its spinal neural network, called a central pattern generator (CPG). Simpler, alternative controllers can be evolved which provide improved performance over the biological prototype (modelled by Ekeberg). Results of computational evolutions demonstrate several possible outcomes exist, with reduced connectivity (16 connections instead of 26) and a diminished equation set for describing the model. Furthermore, resulting oscillators operate over a wider frequency range (0.99 – 12.67 Hz), outperforming the biological prototype (frequencies 1.74 – 5.56 Hz). Evolving advanced yet simpler controllers provides solutions which are more attainable in silicon (VLSI), determines the extent to which nature’s solutions are unique and generates efficient task-specific versions.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11550907_163 .
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Patel, L.N., Hallam, J., Murray, A. (2005). Improved, Simpler Neural Controllers for Lamprey Swimming. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3697. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550907_70
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DOI: https://doi.org/10.1007/11550907_70
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