TL;DR
This paper introduces cellular automata, covering deterministic and probabilistic types, their properties, and applications in modeling phenomena like epidemics, forest fires, and ecosystems, with emphasis on simulation techniques and phase transitions.
Contribution
It provides a comprehensive overview of cellular automata theory, including new insights into their dynamical properties and applications in biological and ecological modeling.
Findings
Deterministic automata exhibit complex dynamical behaviors.
Probabilistic automata relate to Markov processes and phase transitions.
Simulation techniques enable modeling of real-world phenomena.
Abstract
An introduction to cellular automata (both deterministic and probabilistic) with examples. Definition of deterministic automata, dynamical properties, damage spreading and Lyapunov exponents; probabilistic automata and Markov processes, nonequilibrium phase transitions, directed percolation, diffusion; simulation techniques, mean field. Investigation themes: life, epidemics, forest fires, percolation, modeling of ecosystems and speciation. They represent my notes for the school "Dynamical Modeling in Biotechnologies", ISI, Villa Gualino 1996.
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Taxonomy
TopicsCellular Automata and Applications