Informational Principles of Perception-Action Loops and Collective Behaviours

Living beings, robotic and software artefacts can all be seen as agents acting and per-ceiving within an environment. When observed under that perspective, a new concept is accessible: information in the sense of Shannon. It has long been known that information and control are interrelated concepts. However it is only recently that this perspective has been better understood and used in order to study cognition. In this thesis, we build upon such an information-theoretic perspective and add some biologically motivated assumptions. They introduce various constraints on the capture, the processing, or the storage of information by an agent. Using such constraints it is pos-sible to understand some limits on the control abilities of agents, and to derive algorithms that optimize these abilities. More specifically this thesis uses the recently introduced concept of empowerment, i.e. the ability to act upon the environment and perceive back the changes through the sensors. Maximizing this quantity leads to a wide range of cognitively interesting properties. This work studies some of these properties. One of them, the ability to capture informatio