Designing convergent cellular automata.

Jones, David; McWilliam, Richard; Purvis, Alan

Abstract

Cellular automata (CA) have been used by biologists to study dynamic non-linear systems where the interaction between cell behaviour and end-pattern is investigated. It is difficult to achieve convergence of a CA towards a specific static pattern and a common solution is to use genetic algorithms and evolve a ruleset that describes cell behaviour. This paper presents an alternative means of designing CA to converge to specific static patterns. A matrix model is introduced and analysed then a design algorithm is demonstrated. The algorithm is significantly less computationally intensive than equivalent evolutionary algorithms, and not limited in scale, complexity or number of dimensions.

• Journal Article Type: Article
• Publication Date: 2008-12
• Journal: BioSystems
• Print ISSN: 0303-2647
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 96
• Issue: 1
• Pages: 80-85
• DOI: https://doi.org/10.1016/j.biosystems.2008.12.001
• Keywords: Morphogenesis, Convergence, Cellular Automata
• Public URL: https://durham-repository.worktribe.com/output/1530743