Quantifying the complexity of Boolean networks
Josh Socolar, Duke University - Physics
We study two measures of the complexity of heterogeneous extended systems, taking random Boolean networks as prototypical cases. A measure defined by Shalizi et al. for cellular automata, based on a criterion for optimal statistical prediction [Shalizi et al., Phys. Rev. Lett. 93, 118701 (2004)], does not distinguish between the spatial inhomogeneity of dynamically ordered phases and the more irregular behavior of dynamically disordered behavior. We consider a modification in which complexities of individual nodes are calculated, where individual nodes with high complexity are the ones that pass the most information from the past to the future. The complexity of a node depends in a nontrivial way on both the Boolean function of a given node and its location within the network. A network of prisoner's dilemma players is used as an illustrative example. This talk will focus on the conceptual aspects of the work rather than the technical details.
February, 18 2014 | 12:30 - 2:00 | 230E Gross Hall