An algorithm of finding rules for a class of cellular automata
by Lei Kou; Fangfang Zhang; Luobing Chen; Wende Ke; Quande Yuan; Junhe Wan; Zhen Wang
International Journal of Bio-Inspired Computation (IJBIC), Vol. 21, No. 4, 2023

Abstract: A cellular automata (CA) is an important modelling paradigm for complex systems. In the design of CA, the most difficult task is to find the transformation rules that describe the temporal evolution or pattern of a modelled system. A CA with weights (CAW) yields transition rules algorithm is proposed in this paper, which has ample physical meanings and extend the category of CA. Firstly, the weights are increased to connect the updated cell and its neighbours, and the output of each cell depends on the states of cells in the neighbourhood and their respective weights. Secondly, the error correction algorithm is adopted to find correct transition rules by adjusting weights. When the error is zero, the required transition rules with correct weights will be found to describe the fixed configuration. The CAW with the correct rules will relax to the fixed configuration regardless of the initial states. Finally, the mathematical analysis and simulation are carried out with one-dimensional CAW, and the results show that the proposed algorithm has the ability to find correct transition rules as the error converges exponentially.

Online publication date: Wed, 09-Aug-2023

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