This is the codebase for computing effective information (ei), the minimum information partition (MIP), integrated information (phi), and other measures related to the Information Integration Theory of Consciousness (IITC). This is code underlying my http://thesis.library.caltech.edu/8041/. It computes psi measure and is by far the fastest implementation of Balduzzi-Tononi-2008 phi. The major restrictions about the code are:
- It only works for networks of DETERMINISTIC, BINARY nodes.
- It only works for networks with <= 32 nodes.
Directly Relevant Academic Papers
Relationship between IIT and other fields
& The C++ BOOST library from http://boost.org -- particularly boost/foreach.hpp . If on a mac, you can install these using 'macports' or 'homebrew'.
Run the command 'recompile', which generates an executable 'consciousness'. I.e.,
$ ./recompile $ ./consciousness filename.txt
Computes the measures for the system specified in filename.txt
The directory "e/" contains example systems to compute the phi/psi. For example, to compute the measures for the system "transitions/3RN.txt", you'd do:
$ ./consciousness e/transitions/3RN.txt
The directory 'balduzzi_python' contains the original python code from David Balduzzi to compute the phi in the 2008 paper, "Integrated Information in Discrete Dynamical Systems". The directory 'tests' is a series of simple programs that spit out system diagnostic information. It's unlikely you'll ever need them. You can safely ignore this directory.