Abstract
Random Boolean networks are a widely acknowledged model for cell dynamics. Previous studies have shown the possibility of achieving Boolean networks with given characteristics by means of evolutionary techniques. In this work we make a further step towards more biologically plausible models by aiming at evolving networks with a given fraction of active nodes along the attractors, while constraining the evolutionary process to move across critical networks. Results show that this path along criticality does not impede to climb the mount of improbable, yet biologically realistic requirements.
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Notes
- 1.
In other words, we aim to obtain a divergence between the grey level and the Boolean functions’ bias, being not interested in reaching a particular final grey level
- 2.
The position of these mutations within the string coding the individuals is randomly chosen, whereas their direction (0 → 1 or 1 → 0) is predisposed to reach the desired bias.
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Magrì, S., Villani, M., Roli, A., Serra, R. (2019). Evolving Critical Boolean Networks. In: Cagnoni, S., Mordonini, M., Pecori, R., Roli, A., Villani, M. (eds) Artificial Life and Evolutionary Computation. WIVACE 2018. Communications in Computer and Information Science, vol 900. Springer, Cham. https://doi.org/10.1007/978-3-030-21733-4_2
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