Fisher information at the edge of chaos in random boolean networks

X. Rosalind Wang*, Joseph T. Lizier, Mikhail Prokopenko

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)


We study the order-chaos phase transition in random Boolean networks (RBNs), which have been used as models of gene regulatory networks. In particular, we seek to characterize the phase diagram in information-theoretic terms, focusing on the effect of the control parameters (activity level and connectivity). Fisher information, which measures how much system dynamics can reveal about the control parameters, offers a natural interpretation of the phase diagram in RBNs. We report that this measure is maximized near the order-chaos phase transitions in RBNs, since this is the region where the system is most sensitive to its parameters. Furthermore, we use this study of RBNs to clarify the relationship between Shannon and Fisher information measures.

Original languageEnglish
Pages (from-to)315-329
Number of pages15
JournalArtificial Life
Issue number4
Publication statusPublished - Oct 2011
Externally publishedYes


  • Edge of chaos
  • Fisher information
  • Phasetransition
  • Random Boolean networks
  • Shannon information

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