InforLorV4, Main, Exploration, bibRecord, 000D20

A Metric for Evolving 2-D Cellular Automata As Pseudo-Random Number Generators

Identifieur interne : 000D20 ( Main/Exploration ); précédent : 000D19; suivant : 000D21

A Metric for Evolving 2-D Cellular Automata As Pseudo-Random Number Generators

Auteurs : Nikolaos Vlassopoulos [Grèce] ; Bernard Girau [France]

Source :

Journal of Cellular Automata [ 1557-5969 ] ; 2014.

RBID : Hal:hal-01071871

Abstract

In this paper we study the problem of evolving 2-dimensional Cellular Automata (CA) as Pseudo-random Number Generators (PRNG). First, we introduce a composite fitness metric that incorporates elements from PRNG tests, and which is more suitable for evolving CA. Second, we apply and verify this composite metric on two different use-cases: First, to evolve Additive CA as PRNGs using Genetic Algorithms and second, to evolve Totalistic CA as PRNGs using a Markov Chain Monte-Carlo approach.

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https://hal.inria.fr/hal-01071871

Affiliations:

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Le document en format XML

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<front><div type="abstract" xml:lang="en">In this paper we study the problem of evolving 2-dimensional Cellular Automata (CA) as Pseudo-random Number Generators (PRNG). First, we introduce a composite fitness metric that incorporates elements from PRNG tests, and which is more suitable for evolving CA. Second, we apply and verify this composite metric on two different use-cases: First, to evolve Additive CA as PRNGs using Genetic Algorithms and second, to evolve Totalistic CA as PRNGs using a Markov Chain Monte-Carlo approach.</div>
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A Metric for Evolving 2-D Cellular Automata As Pseudo-Random Number Generators

A Metric for Evolving 2-D Cellular Automata As Pseudo-Random Number Generators

Source :

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

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