Evolving Robust Asynchronous Cellular Automata for the Density Task
Marco Tomassini
Mattias Venzi
Computer Science Institute,
University of Lausanne,
1015 Lausanne, Switzerland
Abstract
In this paper the evolution of three kinds of asynchronous cellular automata are studied for the density task. Results are compared with those obtained for synchronous automata and the influence of various asynchronous update policies on the computational strategy is described. How synchronous and asynchronous cellular automata behave is investigated when the update policy is gradually changed, showing that asynchronous cellular automata are more adaptable. The behavior of synchronous and asynchronous evolved automata are studied under the presence of random noise of two kinds and it is shown that asynchronous cellular automata implicitly offer superior fault tolerance.
