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Computational Complexity pp 1564–1575Cite as

Identification of Cellular Automata

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Article Outline

Glossary

Definition of the Subject

Introduction

Background and Basics of Identification

Identification Using Machine Learning

Identification Using Polynomial Representation

Binary Tree Representations and Genetic Programming

Identification Using Decision Trees

Identification by Immunocomputing

Application of Identification in Automatic Design of Cellular‐Automata Processors

Future Directions

Bibliography

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Abbreviations

Cellular automaton:

is an array of finite automata connected locally, which update their states in discrete time and at the same moments; every automaton updates its next state depending on the states of its closest neighbors.

Decision tree:

is a mapping from a classified set of observations about an event to the conclusion about its outcome.

Deterministic automaton:

has only one next state for each pair of internal and input states.

Finite automaton:

is an abstract machine which takes a finite number of states and transitions between the states; the machine changes its states depending on the input states.

Immunocomputing:

replicates principles of information processing by immune networks to perform computation.

Learning automaton:

modifies its transition rules depending on its past experience.

Learning classifier system:

is a rule‐based system, a population of rules, which are processed, selected and updated using reinforcement learning techniques.

Machine learning:

is a subfield of artificial intelligence concerned with the design and development of algorithms and techniques that allow computers to learn – to improve automatically through experience.

Orthogonalization:

is subdividing a system into its distinct components.

Polynomial representation:

of cell‐state transition rules interpret local transition rules of a cellular automaton as a Boolean or arithmetic polynomial.

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Author information

Authors and Affiliations

  1. Computing, Engineering and Mathematical Sciences, University of the West of England, Bristol, UK

    Andrew Adamatzky

Authors
  1. Andrew Adamatzky
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Editor information

Editors and Affiliations

  1. RAMTECH LIMITED, 122 Escalle Lane, Larkspur, CA, 94939, USA

    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

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Adamatzky, A. (2012). Identification of Cellular Automata. In: Meyers, R. (eds) Computational Complexity. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1800-9_100

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