Amoeba Neurocomputing

Dynamic Structure - Larger

Physarum - multiplication behaviour for resource allocation

Physarum on Water Surface

Pseudopod Extension Towards Chemotactic Stimuli

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Amoeba-Based NeuroComputing
Masashi AONO, RIKEN Advanced Science Institute, Japan

Summary: We created a computing system incorporating an amoeboid unicellular organism (a plasmodium of true slime mould Physarum polycephalum) known to exhibit rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. Introducing an optical feedback according to a recurrent neural network model, we lead the amoeba's photosensitive branches to expand or shrink within a network- patterned chamber in search of a solution to the traveling salesman problem (TSP). Here we demonstrate how our system solves four-city TSP. Our system reached and stabilized an optimal solution, as the amoeba having photoavoidance response changed its shape in search for the most stable configuration allowing the amoeba to maximize its body area while minimizing the risk of being illuminated. Intriguingly, the maintained stabilizing mode of the solution, however, spontaneously switched to the destabilizing mode without any explicit external perturbation. Contrary to the photoavoidance response, the amoeba started to destabilize the once-reached solution by spontaneously expanding its branch under illumination, and restarted the solution- searching process. Consequently, our system found three solutions within 16h observation by repeatedly switching between the stabilizing and destabilizing modes.

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