In this work we address the issue of designing a Boolean network such that its attractors are maximally distant. The design objective is converted into an optimisation problem, that is solved via an iterated local search algorithm. This technique proves to be effective and enables us to design networks with size up to 200 nodes. We also show that the networks obtained through the optimisation technique exhibit a mixture of characteristics typical of networks in the critical and chaotic dynamical regime.

Stochastic Local Search to Automatically Design Boolean Networks with Maximally Distant Attractors / S. Benedettini; A. Roli; M. Villani; R. Serra. - STAMPA. - 6624:(2011), pp. 22-31. (Intervento presentato al convegno EvoStar 2011 tenutosi a Torino (Italy) nel 27-29 April 2011) [10.1007/978-3-642-20525-5_3].

Stochastic Local Search to Automatically Design Boolean Networks with Maximally Distant Attractors

BENEDETTINI, STEFANO;ROLI, ANDREA;
2011

Abstract

In this work we address the issue of designing a Boolean network such that its attractors are maximally distant. The design objective is converted into an optimisation problem, that is solved via an iterated local search algorithm. This technique proves to be effective and enables us to design networks with size up to 200 nodes. We also show that the networks obtained through the optimisation technique exhibit a mixture of characteristics typical of networks in the critical and chaotic dynamical regime.
2011
Applications of Evolutionary Computation, Part I
22
31
Stochastic Local Search to Automatically Design Boolean Networks with Maximally Distant Attractors / S. Benedettini; A. Roli; M. Villani; R. Serra. - STAMPA. - 6624:(2011), pp. 22-31. (Intervento presentato al convegno EvoStar 2011 tenutosi a Torino (Italy) nel 27-29 April 2011) [10.1007/978-3-642-20525-5_3].
S. Benedettini; A. Roli; M. Villani; R. Serra
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/114788
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