Solving mazes with memristors: A massively parallel approach
Abstract
Solving mazes is not just a fun pastime: They are prototype models in several 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 nontrivial 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 multiplesolution mazes and sorts out the solution paths according to their length. Our results demonstrate not only the application of memristive networks to the field of massively parallel computing, but also an algorithm to solve mazes, which could find applications in different fields.
 Publication:

Physical Review E
 Pub Date:
 October 2011
 DOI:
 10.1103/PhysRevE.84.046703
 arXiv:
 arXiv:1103.0021
 Bibcode:
 2011PhRvE..84d6703P
 Keywords:

 02.70.c;
 87.18.Sn;
 73.50.Fq;
 73.63.b;
 Computational techniques;
 simulations;
 Neural networks;
 Highfield and nonlinear effects;
 Electronic transport in nanoscale materials and structures;
 Condensed Matter  Mesoscale and Nanoscale Physics;
 Computer Science  Emerging Technologies;
 Physics  Computational Physics
 EPrint:
 Phys. Rev. E 84, 046703 (2011)