We propose asynchronous cellular automata fashioned model of true slime mold Physarum polycephalum plasmodium equipped with a dynamic feedback mechanism based on Bayesian and inverse Bayesian inference. These are implemented as feedback from dynamical protoplasmic flow into local tubular structures in slime mold. Because inverse Bayesian inference replaces conditional probabilities with empirical ones and relaxes the probability space, the model can behave robustly and adaptively. We describe a brief overview of our model in this paper.

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© 2023 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license
2023
Massachusetts Institute of Technology
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Issue Section:
General Conference