A Mapping Function to Use Cellular Automata for Solving MAS Problems

Cellular automata are a very powerful and well researched area in computer science. We use approaches from the cellular automata research to solve optimization problems in the multi agent system research area. For this purpose, we require a transformation from agents located in an Euclidean space into an abstract cell assignment for cellular automata. In this paper, a mapping function is presented and evaluated with a reverse function. This function can be calculated by each agent individually based only on local information. Additionally, we examine the performance of the function in inexact and non-deterministic environments.

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