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Solving mazes with memristors: a massively-parallel approach

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AbstractSolving mazes is not just a fun pastime. Mazes are prototype models in graph theory, topology, robotics, traffic optimization, psychology, and in many other areas of science and technology. However, when maze complexity increases their solution becomes cumbersome and very time consuming. Here, we show that a network of memristors - resistors with memory - can solve such a non-trivial problem quite easily. In particular, maze solving by the network of memristors occurs in a massively parallel fashion since all memristors in the network participate simultaneously in the calculation. The result of the calculation is then recorded into the memristors’ states, and can be used and/or recovered at a later time. Furthermore, the network of memristors finds all possible solutions in multiple-solution mazes, and sorts out the solution paths according to their length. Our results demonstrate not only the first application of memristive networks to the field of massively-parallel computing, but also a novel algorithm to solve mazes which could find applications in different research fields.
Springer Science and Business Media LLC
Title: Solving mazes with memristors: a massively-parallel approach
Description:
AbstractSolving mazes is not just a fun pastime.
Mazes are prototype models in graph theory, topology, robotics, traffic optimization, psychology, and in many other areas of science and technology.
However, when maze complexity increases their solution becomes cumbersome and very time consuming.
Here, we show that a network of memristors - resistors with memory - can solve such a non-trivial problem quite easily.
In particular, maze solving by the network of memristors occurs in a massively parallel fashion since all memristors in the network participate simultaneously in the calculation.
The result of the calculation is then recorded into the memristors’ states, and can be used and/or recovered at a later time.
Furthermore, the network of memristors finds all possible solutions in multiple-solution mazes, and sorts out the solution paths according to their length.
Our results demonstrate not only the first application of memristive networks to the field of massively-parallel computing, but also a novel algorithm to solve mazes which could find applications in different research fields.

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