Amoeba-inspired Computing Paradigm: Ultrahigh Efficiency Problem Solving Utilizing Spatiotemporal Dynamics

Presto Researcher

Masashi Aono

Keio University
Associate Professor

Research Outline

Inspired by spatiotemporal dynamics of an amoeboid organism that adapts to the environment highly efficiently, I formulated the “amoeba model”, which outperforms dramatically one of the most fastest stochastic local search algorithms for searching for a solution to a representative combinatorial optimization problem, the satisfiability problem. By implementing the amoeba model using various nanodevices such as nanoelectronics elements and quantum dots, I aim at systematizing a methodology for developing ultracompact and ultralow-power-consumption devices, which are useful for diverse applications including protein structure prediction.

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