Stochastic Local Search to Automatically Design Boolean Networks with Maximally Distant Attractors
Conference Paper
Publication Date:
2011
Short description:
Stochastic Local Search to Automatically Design Boolean Networks with Maximally Distant Attractors / Stefano, Benedettini; Andrea, Roli; Serra, Roberto; Villani, Marco. - STAMPA. - 6624:1(2011), pp. 22-31. ( International Conference on the Applications of Evolutionary Computation, EvoApplications 2011 Torino, ita april 2011) [10.1007/978-3-642-20525-5_3].
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
Iris type:
Relazione in Atti di Convegno
Keywords:
random Boolean network; dynamical model; dynamical systems
List of contributors:
Stefano, Benedettini; Andrea, Roli; Serra, Roberto; Villani, Marco
Book title:
Applications of Evolutionary Computation
Published in: