Predictive Coding-based Deep Dynamic Neural Network for Visuomotor Learning

by   Jungsik Hwang, et al.

This study presents a dynamic neural network model based on the predictive coding framework for perceiving and predicting the dynamic visuo-proprioceptive patterns. In our previous study [1], we have shown that the deep dynamic neural network model was able to coordinate visual perception and action generation in a seamless manner. In the current study, we extended the previous model under the predictive coding framework to endow the model with a capability of perceiving and predicting dynamic visuo-proprioceptive patterns as well as a capability of inferring intention behind the perceived visuomotor information through minimizing prediction error. A set of synthetic experiments were conducted in which a robot learned to imitate the gestures of another robot in a simulation environment. The experimental results showed that with given intention states, the model was able to mentally simulate the possible incoming dynamic visuo-proprioceptive patterns in a top-down process without the inputs from the external environment. Moreover, the results highlighted the role of minimizing prediction error in inferring underlying intention of the perceived visuo-proprioceptive patterns, supporting the predictive coding account of the mirror neuron systems. The results also revealed that minimizing prediction error in one modality induced the recall of the corresponding representation of another modality acquired during the consolidative learning of raw-level visuo-proprioceptive patterns.


Seamless Integration and Coordination of Cognitive Skills in Humanoid Robots: A Deep Learning Approach

This study investigates how adequate coordination among the different co...

Generating goal-directed visuomotor plans based on learning using a predictive coding type deep visuomotor recurrent neural network model

The current paper presents how a predictive coding type deep recurrent n...

Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model

The current paper proposes a novel predictive coding type neural network...

A Dynamic Neural Network Approach to Generating Robot's Novel Actions: A Simulation Experiment

In this study, we investigate how a robot can generate novel and creativ...

AFA-PredNet: The action modulation within predictive coding

The predictive processing (PP) hypothesizes that the predictive inferenc...

Pyramidal Predictive Network: A Model for Visual-frame Prediction Based on Predictive Coding Theory

Visual-frame prediction is a pixel-dense prediction task that infers fut...

Please sign up or login with your details

Forgot password? Click here to reset