Vittorio Sanguineti

Computational joint action: dynamical models to understand the development of joint coordination

This paper introduces a computational model based on game theory and Bayesian estimation to understand how joint coordination develops over repeated trials in human dyads.

Self-operated stimuli improve subsequent visual motion processing

The paper shows that motor learning improves visual motion perception through self-operated stimuli, with perceptual changes linked to internal representation fine-tuning.

Incomplete information about the partner affects the development of collaborative strategies in joint action

The paper shows that incomplete information about a partner slows collaboration learning and leads to alternating leader-follower roles, while reliable information promotes synchronous collaboration.