Langer, Carlotta and Nihat Ay
An embodied agent, that performs a goal-directed action, influences its environment and gets influenced by it. Hence information flows not only among the agents control mechanisms, but also between the agent and its environment. In this article we combine different methods in order to create a framework in which we are able to closely examine the information flow among the body, brain and environment of an agent. We test this framework in a simple experimental setup. There the agents do not learn to perform a task, but we calculate the optimal behavior using the method Planning as Inference, in which the information geometric em-algorithm is used to optimize the likelihood of the goal. Then we analyze the resulting distribution using in- formation theoretic methods including measures corresponding to the concepts of Morphological Computation and Integrated Information Theory. Comparing the behavior of these measures under changing morphological circumstances highlights the asymmetric relationship between these two concepts.