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Springer Probabilistic Cellular Automata: Theory, Applications, Future - Springer

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Description

Probabilistic Cellular Automata (PCA) bridges statistical mechanics, probability theory, computational biology and computer science through advanced modelling of complex systems. This comprehensive volume examines PCA as extensions of classical Cellular Automata, distinguished by their random updating rules that enable flexible numerical computation and realistic simulation of phenomena driven by large-scale neighbour interactions. PCA serve as powerful tools across diverse fields from pure probability through applied domains, offering researchers and practitioners innovative approaches to modelling complex behaviour in systems where stochasticity plays a central role. The book synthesises theory and applications, making it essential for those developing simulation tools or studying computational complexity in biological and physical systems.

Key Features

Probabilistic Cellular Automata framework combines statistical mechanics with probability theory for modelling complex systems.

Random updating rules distinguish PCA from standard Cellular Automata, enabling flexible numerical constructions and realistic simulations.

Applications span computational biology, computer science and probability theory, addressing phenomena driven by large-scale interactions.

Springer publication provides comprehensive coverage of both theoretical foundations and practical applications of PCA methodologies.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
24 January 2019
Listed Since
23 January 2019

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