Closing probabilities in the Kauffman model: An annealed computation

U. Bastolla; G. Parisi

doi:10.1016/0167-2789(96)00060-7

Closing probabilities in the Kauffman model: An annealed computation

U. Bastolla^*
, G. Parisi

^*Corresponding author for this work

University of Rome La Sapienza

Research output: Contribution to journal › Article › peer-review

51 Scopus citations

Abstract

We use a probabilistic approach to compute the distributions of periods, transients and weights of attraction basins in Kauffman networks. The results for these quantities are obtained in the framework of the annealed approximation, first introduced by Derrida and Pomeau. Numerical results for the average periods are in good agreement with the computed values of the exponents. We report also on some interesting features which cannot be explained within the annealed approximation.

Original language	English
Pages (from-to)	1-25
Number of pages	25
Journal	Physica D: Nonlinear Phenomena
Volume	98
Issue number	1
DOIs	https://doi.org/10.1016/0167-2789(96)00060-7
State	Published - 1996
Externally published	Yes

Keywords

Cellular automata
Disordered systems
Genetic regulatory networks
Random boolean networks

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10.1016/0167-2789(96)00060-7

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abstract = "We use a probabilistic approach to compute the distributions of periods, transients and weights of attraction basins in Kauffman networks. The results for these quantities are obtained in the framework of the annealed approximation, first introduced by Derrida and Pomeau. Numerical results for the average periods are in good agreement with the computed values of the exponents. We report also on some interesting features which cannot be explained within the annealed approximation.",

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AB - We use a probabilistic approach to compute the distributions of periods, transients and weights of attraction basins in Kauffman networks. The results for these quantities are obtained in the framework of the annealed approximation, first introduced by Derrida and Pomeau. Numerical results for the average periods are in good agreement with the computed values of the exponents. We report also on some interesting features which cannot be explained within the annealed approximation.

KW - Cellular automata

KW - Disordered systems

KW - Genetic regulatory networks

KW - Random boolean networks

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U2 - 10.1016/0167-2789(96)00060-7

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JO - Physica D: Nonlinear Phenomena

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Closing probabilities in the Kauffman model: An annealed computation

Abstract

Keywords

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