Maximization of Potential Information Flow as a Universal Utility for Collective Behaviour

P. Capdepuy, D. Polani, C.L. Nehaniv

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Citations (Scopus)
35 Downloads (Pure)


We explore how information theoretic quantities
such as potential information flow (empowerment) can be used
as a drive toward complex collective behaviour in the context
of multi-agent systems. In a first experiment, we investigate
the empowerment of two agents interacting in a grid world.
We show that some conditions lead to higher empowerment
than others, depending on the amount of interaction and the
amount of information shared by the agents. We then investigate
more deeply the tradeoff between freedom of the agents and the
constraints they impose on each other. We show that there exist a
trade-off between these where empowerment is maximized. In a
third experiment, we show that agents behaving so as to maximize
potential information transfer over time generate a wide range of
complex collective behaviours. We then discuss how these notions
can be compared to what happens in natural systems.
Original languageEnglish
Title of host publicationProcs of the 2007 IEEE Symposium on Artificial Life (CI-ALife 2007)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Publication statusPublished - 2007


Dive into the research topics of 'Maximization of Potential Information Flow as a Universal Utility for Collective Behaviour'. Together they form a unique fingerprint.

Cite this