2011/03/31 by Yuriy V. Pershin, Massimiliano Di Ventra · 167 citations
Computer Science · Engineering · Mathematics · Neuroscience · Physics and Astronomy · #Advanced Memory and Neural Computing #Artificial intelligence #Computer science #Electrical engineering #Engineering #Graph #Graph theory #Massively parallel #Mathematics #Memristor #Neuroscience and Neural Engineering #Parallel computing #Photoreceptor and optogenetics research #Theoretical computer science #Topology (electrical circuits) #cond-mat.mes-hall #cs.ET #physics.comp-ph
paper · pdf · doi:10.1103/physreve.84.046703
published in Physical Review E 84(4), 046703 (American Physical Society)
arxiv created 2011/07/16 · openalex publication_date 2011/10/14 · arxiv updated 2011/10/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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 multiple-solution 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.