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Simulation of Biological Processes Using Asynchronous Cellular Automata and Machine Learning
Kališ, Vojtěch ; Bidlo, Michal (oponent) ; Fritz, Karel (vedoucí práce)
This thesis explores the fusion of asynchronous cellular automata and machine learning techniques for simulating complex biological processes. Its main focus is on showcasing the inherent potential of a computational framework constructed through combining the parallelism of an asynchronous cellular automata updating model with the predictive capabilities of machine learning algorithms. This study aims to demonstrate the qualities of such hybrid approach by implementing three mathematical cellular automata models of increasing complexity—that is, listed based on their level of complexity, Conway’s Game of Life, SmoothLife and Lenia—in their basic form and then integrate machine learning into the function of the latter two, comparing the results of both approaches afterwards.

Viz též: podobná jména autorů
2 Kališ, Vladimír
2 Kališ, Vladislav
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