Bidirectional Interaction between Visual and Motor Generative Models using Predictive Coding and Active Inference

Louis Annabi (1) , Alexandre Pitti (1) , Mathias Quoy (1)

1 ETIS - UMR 8051 - Equipes Traitement de l'Information et Systèmes

In this work, we build upon the Active Inference (AIF) and Predictive Coding (PC) frameworks to propose a neural architecture comprising a generative model for sensory prediction, and a distinct generative model for motor trajectories. We highlight how sequences of sensory predictions can act as rails guiding learning, control and online adaptation of motor trajectories. We furthermore inquire the effects of bidirectional interactions between the motor and the visual modules. The architecture is tested on the control of a simulated robotic arm learning to reproduce handwritten letters.

Mots clés: visuo-motor control; predictive coding; active inference; developmental robotics; embodiment

Domaines: Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]; Réseau de neurones [cs.NE]

Louis Annabi, Alexandre Pitti, Mathias Quoy. Bidirectional Interaction between Visual and Motor Generative Models using Predictive Coding and Active Inference. 2021. ⟨hal-03201766⟩