£107.98

Springer Probabilistic Cellular Automata - Complexity & Theory

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Description

Expand your understanding of complex systems with Probabilistic Cellular Automata: Theory, Applications and Future Perspectives. This academic volume from the Emergence, Complexity and Computation series provides a deep look into PCA models through the lenses of statistical mechanics, probability theory, computational biology, and computer science. Unlike standard cellular automata, PCA utilize random updating rules to model systems more accurately. This probabilistic component makes them highly effective for complex numerical constructions and realistic simulations of phenomena driven by interactions between large numbers of neighboring structures. Whether you are researching computational biology or studying the foundations of computer science, this book offers the theoretical framework and practical perspectives needed to explore these evolving models.

Key Features

Explores Probabilistic Cellular Automata from multiple academic perspectives including statistical mechanics and probability theory.

Covers practical applications in fields such as computational biology and computer science.

Analyzes PCA as extensions of standard cellular automata models using random updating rules.

Provides tools for complex numerical constructions through probabilistic computing components.

Offers realistic simulation methods for studying phenomena driven by large-scale neighbor interactions.

Product Specifications

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

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