An active inference model of hierarchical action understanding, learning and imitation

Phys Life Rev. 2023 Sep:46:92-118. doi: 10.1016/j.plrev.2023.05.012. Epub 2023 Jun 5.

Abstract

We advance a novel active inference model of the cognitive processing that underlies the acquisition of a hierarchical action repertoire and its use for observation, understanding and imitation. We illustrate the model in four simulations of a tennis learner who observes a teacher performing tennis shots, forms hierarchical representations of the observed actions, and imitates them. Our simulations show that the agent's oculomotor activity implements an active information sampling strategy that permits inferring the kinematic aspects of the observed movement, which lie at the lowest level of the action hierarchy. In turn, this low-level kinematic inference supports higher-level inferences about deeper aspects of the observed actions: proximal goals and intentions. Finally, the inferred action representations can steer imitative responses, but interfere with the execution of different actions. Our simulations show that hierarchical active inference provides a unified account of action observation, understanding, learning and imitation and helps explain the neurobiological underpinnings of visuomotor cognition, including the multiple routes for action understanding in the dorsal and ventral streams and mirror mechanisms.

Keywords: Action representation; Action understanding; Active inference; Hierarchical model; Visuomotor control.

Publication types

  • Review

MeSH terms

  • Cognition / physiology
  • Imitative Behavior* / physiology
  • Intention
  • Learning* / physiology
  • Movement / physiology