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Probabilistic Cellular Automata - novo libro

2018, ISBN: 9783319655581

Theory, Applications and Future Perspectives, eBooks, eBook Download (PDF), 1st ed. 2018, [PU: Springer International Publishing], Springer International Publishing, 2018

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Probabilistic Cellular Automata: Theory, Applications and Future Perspectives Pierre-Yves Louis Editor
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9783319655581

Dados detalhados do livro - Probabilistic Cellular Automata: Theory, Applications and Future Perspectives Pierre-Yves Louis Editor


EAN (ISBN-13): 9783319655581
ISBN (ISBN-10): 3319655582
Ano de publicação: 2018
Editor/Editora: Springer-Verlag New York, LLC Digital >16

Livro na base de dados desde 2018-03-16T11:15:17+00:00 (Lisbon)
Página de detalhes modificada pela última vez em 2024-03-31T09:32:21+01:00 (Lisbon)
Número ISBN/EAN: 9783319655581

Número ISBN - Ortografia alternativa:
3-319-65558-2, 978-3-319-65558-1
Ortografia alternativa e termos de pesquisa relacionados:
Autor do livro: nardi, louis
Título do livro: automata

Dados da editora

Autor: Pierre-Yves Louis; Francesca R. Nardi
Título: Emergence, Complexity and Computation; Probabilistic Cellular Automata - Theory, Applications and Future Perspectives
Editora: Springer; Springer International Publishing
344 Páginas
Ano de publicação: 2018-02-21
Cham; CH
Língua: Inglês
149,79 € (DE)
154,00 € (AT)
177,00 CHF (CH)
Available
XVIII, 344 p. 89 illus., 67 illus. in color.

EA; E107; eBook; Nonbooks, PBS / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; high-dimensional interacting stochastic systems; dynamical systems; multiscale models; complex systems; individual-based stochastic models; agent-based modelling; decentralised computational systems; synchronous/asynchronous updating; resilience to asynchronism; density classiffication; emergence of collective behaviour; self-organisation; bootstrap percolation; crisis propagation; equilibrium and non-equilibrium statistical mechanics; phase transition; metastability; finite range and mean field interactions; reaction-diffusion; complexity; B; Probability Theory; Applied Dynamical Systems; Mathematical and Computational Biology; Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Computational and Systems Biology; Probability and Statistics in Computer Science; Engineering; Stochastik; Mathematik für Ingenieure; Kybernetik und Systemtheorie; DV-gestützte Biologie/Bioinformatik; Mathematik für Informatiker; BB

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.
Offers an 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 Discusses applications in computational (cell) biology, e.g. the Cellular Potts Model and stability of emerging patterns, time to stationarity in simulation algorithms, and transient regimes;
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