Inverting the Interaction Cycle to Model Embodied Agents

Cognitive architectures should make explicit the conceptual begin and end points of the agent/environment interaction cycle. Most architectures begin with the agent receiving input data representing the environment, and end with the agent sending output data. This paper suggests inverting this cycle: the agent sends output data that specifies an experiment, and receives input data that represents the result of this experiment. This complies with the embodiment paradigm because the input data does not directly represent the environment and does not amount to the agent's perception. We illustrate this in an example and propose an assessment method based upon activity-trace analysis.