Abstract
In order to develop an adaptive computing system, we investigate microscopic optical feedback to a group of microbes (Euglena gracilis in this study) with a neural network algorithm, expecting that the unique characteristics of microbes, especially their strategies to survive/adapt against unfavorable environmental stimuli, will explicitly determine the temporal evolution of the microbe-based feedback system. The photophobic reactions of Euglena are extracted from experiments, and built in the Monte-Carlo simulation of a microbe-based neurocomputing. The simulation revealed a good performance of Euglena-based neurocomputing. Dynamic transition among the solutions is discussed from the viewpoint of feedback instability.
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Ozasa, K., Aono, M., Maeda, M., Hara, M. (2009). Simulation of Neurocomputing Based on Photophobic Reactions of Euglena: Toward Microbe–Based Neural Network Computing. In: Calude, C.S., Costa, J.F., Dershowitz, N., Freire, E., Rozenberg, G. (eds) Unconventional Computation. UC 2009. Lecture Notes in Computer Science, vol 5715. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03745-0_24
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DOI: https://doi.org/10.1007/978-3-642-03745-0_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03744-3
Online ISBN: 978-3-642-03745-0
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