An embodied agent influences its environment and is influenced by it. We use the sensorimotor loop to model these interactions and quantify the information flows in the system by information-theoretic measures. This includes a measure for the interaction among the agent’s body and its environment, often referred to as morphological computation. Additionally, we examine the controller complexity, which can be seen in the context of the integrated information theory of consciousness. Applying this framework to an experimental setting with simulated agents allows us to analyze the interaction between an agent and its environment, as well as the complexity of its controller. Previous research revealed that a morphology adapted well to a task can substantially reduce the required complexity of the controller. In this work, we observe that the agents first have to understand the relevant dynamics of the environment to interact well with their surroundings. Hence an increased controller complexity can facilitate a better interaction between an agent’s body and its environment.