Team members: Travis Byrum, Anshuman Swain, Brennan Klein and William F Fagan
R code/package for calculating effective information in networks. This can then be used to search for macroscale representations of a network such that the coarse grained representation has more effective information than the microscale, a phenomenon known as causal emergence (see Klein and Hoel, 2020).
A shiny application is available for demonstration purposes.
library(devtools)
install_github("travisbyrum/einet") #installation
library(igraph)
library(einet)
set.seed(123)
karate_ce <- causal_emergence(karate) #using the karate club network provided within the package
karate_ce #displays all the relevant information about effective information at micro and macro scales, the effectiveness (normalized effective information at micro-scale and teh causal emergence
For detailed information please visit https://github.com/jkbren/einet
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