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Amoeba-Based Emergent Computing: Combinatorial Optimization and Autonomous Meta-Problem Solving
Masashi Aono, Masahiko Hara, Kazuyuki Aihara and Toshinori Munakata

Here we demonstrate a computing system employing an amoeba of a true slime mold Physarum known as a model organism for studying cellular information processing. The system works as a neurocomputer that exhibits high optimization capability in solving various problems including the traveling salesman problem. Additionally, we present a new technique that we call “autonomous meta-problem solving.” In this approach, our system not only can solve a given problem but also can find new problems and then determine solutions by exploiting the amoeba’s unique searching ability and spontaneous behavior.

Keywords: Physarum, actomyosin, molecular computing, self-organization, neural network, optimization, fluctuations, spontaneous destabilization, chaos, meta-problem solving.

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