Ant Colony Optimisation for Performing Computational Task in Cellular Automata

  • Michal Bidlo IT4Innovations Centre of Excellence, Faculty of Information Technology, Brno University of Technology, Czech Republic
  • Jakub Korgo IT4Innovations Centre of Excellence, Faculty of Information Technology, Brno University of Technology, Czech Republic
Keywords: ant colony optimisation, MAX-MIN ant system, cellular automaton, transition function, square calculation


A method is presented for the design of cellular automata rules by means of ant algorithms. In particular, Elitist Ant System and a~modified MAX-MIN Ant System are applied to search for transition functions of 1D cellular automata that are able to calculate squares of given input values. It will be shown that the proposed MAX-MIN Ant System can perform significantly better than the standard variant of Elitist Ant System. In particular, in the most advanced case study, the ant algorithm showed an ability to design a~complete set of elementary cellular automata rules that fulfil the required square calculations. Some selected results will be presented and their features discussed.


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How to Cite
Bidlo, M. and Korgo, J. 2019. Ant Colony Optimisation for Performing Computational Task in Cellular Automata. MENDEL. 25, 1 (Jun. 2019), 147-156. DOI:
Research articles