This paper explores the computational parallels between motor control and social interaction, suggesting that the same principles underlying motor control may be extended to social interaction. The authors examine how motor commands acting on the body can be equated with communicative signals acting on others, and propose that the brain uses internal models to predict and control these interactions. They introduce the MOSAIC model, which involves multiple forward and inverse models to predict and control motor commands and their sensory consequences. This model is extended to a hierarchical version (HMOSAIC) for more complex movements and intentions. The authors argue that the similarity in brain structures across individuals facilitates communication and understanding of others' actions, and suggest that this may underlie the unique capabilities of human communication. They conclude that using the motor system for action understanding is an efficient mechanism for social interaction.This paper explores the computational parallels between motor control and social interaction, suggesting that the same principles underlying motor control may be extended to social interaction. The authors examine how motor commands acting on the body can be equated with communicative signals acting on others, and propose that the brain uses internal models to predict and control these interactions. They introduce the MOSAIC model, which involves multiple forward and inverse models to predict and control motor commands and their sensory consequences. This model is extended to a hierarchical version (HMOSAIC) for more complex movements and intentions. The authors argue that the similarity in brain structures across individuals facilitates communication and understanding of others' actions, and suggest that this may underlie the unique capabilities of human communication. They conclude that using the motor system for action understanding is an efficient mechanism for social interaction.