Embodied communication model in ACT-R based robot

Human communication is mediated by symbolic (e.g., language) or quantitative (e.g., body movements) representations. For smooth interaction between humans and machines, it is important for machines to have a mechanism to convert between symbolic and quantitative representations. In this study, we construct a model in which the cognitive architecture as a symbol processing system and the robot as an embodied media interact with each other. In this model, we use a simple word game with a human as a test case of communication. The conversion from a symbolic to a quantitative representation in this model corresponds to the robot's posture based on the "size image" of a noun. The "size image" is a general human image of a word taken from the word distributional representation. The influence of quantitative representation on symbols in this model is represented by the influence of the robot's posture on the model's next word selection.