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

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

URL: http://arxiv.org/abs/2104.09163v1
Date: Mon, 19 Apr 2021 09:41:31 GMT
Title: Bidirectional Interaction between Visual and Motor Generative Models using Predictive Coding and Active Inference
Authors: Louis Annabi, Alexandre Pitti, Mathias Quoy
Abstract summary: We 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.
Score: 68.8204255655161
License: http://creativecommons.org/licenses/by-sa/4.0/
Abstract: 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.

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