Cellular Automata Applications in Shortest Path Problem
Michail-Antisthenis I. Tsompanas, Nikolaos I. Dourvas, Konstantinos, Ioannidis, Georgios Ch. Sirakoulis, Rolf Hoffmann, Andrew Adamatzky

TL;DR
This paper reviews the use of Cellular Automata (CAs) for solving the shortest path problem across various disciplines, highlighting algorithms, applications, and biological modeling with CA-based approaches.
Contribution
It provides a comprehensive overview of CA-based shortest path algorithms, including a detailed introduction to the first such algorithm and applications in swarm robotics, networks, and biological systems.
Findings
CA algorithms can find shortest paths more efficiently than traditional methods.
CA models successfully mimic biological and robotic pathfinding behaviors.
Applications span computer science, robotics, networks, and biology.
Abstract
Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from…
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Taxonomy
TopicsSlime Mold and Myxomycetes Research · Chemical synthesis and alkaloids
