title: Designing convergent cellular automata.
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.
authors.affiliation: University of Durham, England. d.h.jones2@dur.ac.uk
authors.forename: David H
authors.initials: DH
authors.lastname: Jones
authors.forename: Richard
authors.initials: R
authors.lastname: McWilliam
authors.forename: Alan
authors.initials: A
authors.lastname: Purvis
mesh_terms: D000222:Adaptation, Physiological / Q000502:physiology*; D000465:Algorithms; D002468:Cell Physiological Phenomena / Q000502:physiology*; D003198:Computer Simulation; D008954:Models, Biological