Nihat Ay, Keyan Ghazi-Zahedi

Paper #: 13-10-031

This article deals with the causal structure of an agent’s sensorimotor loop. Of particular interest are causal effects that can be identified from an agent-centric perspective based on in situ observations. Within this identification, the world model of the agent plays a central role. Furthermore, various kinds of information flows through the sensorimotor loop are considered, including causal as well as associational ones. Transfer entropy and predictive information are discussed in more detail. The maximization of the latter leads to coordinated behavior within an experimental case study. Corresponding results on the relation to morphological computation are presented.