Informational Principles of Perception-Action Loops and Collective Behaviours

Living beings, robotic and software artefacts can all be seen as agents acting and perceiving 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 possible 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 information that is relevant for the perception-action loop of the agent, is deeply investigated and algorithms for exploiting this ability are presented. The second part of the thesis deals with the use of the information-theoretic framework when multiple agents are interacting with each other. Empowerment maximization in this context leads to two phenomena: the generation of complex structures, and the emergence of synchronised and potentially cooperative interactions. In this thesis, the first phenomenon is empirically investigated through various spatial scenarios in order to understand the kind of structures that are generated and under which conditions they appear. Connections are made between the second phenomenon and the concept of the multiple-access channel. Using recent developments of this information-theoretic model, it is possible to precisely study the kind of interactions that can occur, and the situations that lead to synchronised or cooperative behaviour. The general aim of this work is to give a comprehensive picture of the information-theoretic framework for studying the perception-action loop, bringing both single and multi-agents aspects together. The concepts presented in this thesis allows one to study some fundamental aspects of cognition, to engineer self-motivated robotic systems, or to drive self-organization in multi-agents systems