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Optimal Control Rules for Random Boolean Networks

  • Matthew R. Karlsen
  • Sotiris K. Moschoyiannis
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 812)

Abstract

A random Boolean network (RBN) may be controlled through the use of a learning classifier system (LCS) – an eXtended Classifier System (XCS) can evolve a rule set that directs an RBN from any state to a target state. However, the rules evolved may not be optimal, in terms of minimising the total cost of the paths used to direct the network from any state to a specified attractor. Here we uncover the optimal set of control rules via an exhaustive algorithm. The performance of an LCS (XCS) on the RBN control problem is assessed in light of the newly uncovered optimal rule set.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Engineering and Physical Sciences, Department of Computer ScienceUniversity of SurreyGuildfordUK

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