Experimental Compositional Analysis of Cellular Automata

Abstract

Cellular automata (for short, CA) are massively parallel systems obtained by composition of myriads of simple agents interacting locally, i.e. with their closest neighbors. In spite of their simplicity, the dynamics of CA is potentially very rich, and ranges from attracting stable configurations to spatiotemporally chaotic features and pseudo-random generation abilities, from very simple forms of destruction of information to more complex ones where information propagates following non-trivial rules [4, 249, 107, 113, 115, 121, 132, 291, 317, 331]; Von Neumann introduced them in order to model biological self-reproducing behaviors [314]. Moreover, from the computational viewpoint, they are universal, that is, as powerful as Turing machines and, thus, classical Von Neumann architectures (see Chap. 9). This motivates our choice to study these highly stuctured systems in more details; we concentrate on two aspects.