Special Issue “Information Processing in Complex Systems” in Journal Entropy.

Featuring 10 articles on the rapidly growing topic of studying complex systems using an information-theoretic viewpoint.

Guest editor Rick Quax: “All systems in nature have one thing in common: they process information. Information is registered in the state of a system and its elements, implicitly and invisibly. As elements interact, information is transferred and modified. Indeed, bits of information about the state of one element will travel—imperfectly—to the state of the other element, forming its new state. This storage, transfer, and modification of information, possibly between levels of a multi level system, is imperfect due to randomness or noise. From this viewpoint, a system can be formalized as a collection of bits that is organized according to its rules of dynamics and its topology of interactions. Mapping out exactly how these bits of information percolate through the system could reveal new fundamental insights in how the parts orchestrate to produce the properties of the system. A theory of information processing would be capable of defining a set of universal properties of dynamical multi level complex systems, which describe and compare the dynamics of diverse complex systems ranging from social interaction to brain networks, from financial markets to biomedicine. Each possible combination of rules of dynamics and topology of interactions, with disparate semantics, would reduce to a single language of information processing.”

Published articles
Published thesis
  • Golub, G. Chliamovitch, A. Dupuis, B. Chopard (accepted) Multiscale Representation of High-Frequency Marked Liquidity. Available at:
  • Górski, P.J., Czaplicka, A., Hołyst, J.A. (accepted) Coevolution of Information Processing and Topology in Hierarchical Adaptive Random Boolean Networks. To: European Physical Journal B. Available at:
  • Har Shemesh, O., Quax, R., Hoekstra, A.G., Sloot, P.M.A. (accepted) Information geometric analysis of phase transitions in complex patterns: the case of the Gray-Scott reaction-diffusion model. To: JSTAT. Available at:
  • G. Siudem, J.A. Holyst (subm) Diffusion on weakly-coupled networks of networks with fitness factors. To: Physical Review E. Available at:
  • Chliamovitch, G., Chopard, B. and L. Velasquez (subm) Assessing complexity by means of maximum entropy models. To: Physical Review E. Available at:
Under Preparation
  • Czaplicka, A., Hołyst, J.A. (subm) From equality to diversity – bottom-up approach for hierarchy growth.  Available at:
Conference contributions


Janusz Holyst: Information slows down hierarchy growth @ essa – Simulating the Social Processes of Science. Thursday, 10 April 2014. View Presentation here.


Janusz Holyst: Information slows down hierarchy growth @ First Annual KnowEscape Conference, November 2013.

Conference Paper:

A. Czaplicka; K. Suchecki; B. Minano; M. Trias and J.A. Holyst: Information slows down hierarchy growth; 7 October 2013.


Criticality and Emergence in Multilevel Systems