Identification Of Probabilistic Cellular Automata

Probabilistic Cellular Automata

This book explores Probabilistic Cellular Automata (PCA) from the perspectives of statistical mechanics, probability theory, computational biology and computer science. PCA are extensions of the well-known Cellular Automata models of complex systems, characterized by random updating rules. Thanks to their probabilistic component, PCA offer flexible computing tools for complex numerical constructions, and realistic simulation tools for phenomena driven by interactions among a large number of neighboring structures. PCA are currently being used in various fields, ranging from pure probability to the social sciences and including a wealth of scientific and technological applications. This situation has produced a highly diversified pool of theoreticians, developers and practitioners whose interaction is highly desirable but can be hampered by differences in jargon and focus. This book – just as the workshop on which it is based – is an attempt to overcome these difference and foster interest among newcomers and interaction between practitioners from different fields. It is not intended as a treatise, but rather as a gentle introduction to the role and relevance of PCA technology, illustrated with a number of applications in probability, statistical mechanics, computer science, the natural sciences and dynamical systems. As such, it will be of interest to students and non-specialists looking to enter the field and to explore its challenges and open issues.

Identification of Probabilistic Cellular Automata

Cellular Automata

This book constitutes the refereed proceedings of the 6th International Conference on Cellular Automata for Research and Industry, ACRI 2004, held in Amsterdam, The Netherlands in October 2004. The 60 revised full papers and 30 poster papers presented were carefully reviewed and selected from 150 submissions. The papers are devoted to methods and theory; evolved cellular automata; traffic, networks, and communication; applications in science and engineering; biomedical applications, natural phenomena and ecology; and social and economical applications.