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Book ChapterDOI

Developmental Dynamics of RNNPB: New Insight about Infant Action Development

TLDR
The analysis of the self-organizing process of the parametric biases revealed an infant-like developmental change in action learning: the RNNPB first adapted to the goal and then to the means, causing this phased development.
Abstract
Developmental studies have suggested that infants’ action is goal-directed. When imitating an action, younger infants tend to reproduce the goal while ignoring the means (i.e., the movement to achieve the goal) whereas older infants can imitate both. We suggest that the developmental dynamics of a Recurrent Neural Network with Parametric Bias (RNNPB) may explain the mechanism of infant development. Our RNNPB model was trained to reproduce six types of actions (2 different goals x 3 different means), during which parametric biases were self-organized to represent the difference with respect to both the goal and means. Our analysis of the self-organizing process of the parametric biases revealed an infant-like developmental change in action learning: the RNNPB first adapted to the goal and then to the means. The different saliency of these two features caused this phased development. We discuss the analogy of our result to infant action development.

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Journal ArticleDOI

Emergence of Altruistic Behavior Through the Minimization of Prediction Error

TL;DR: This work hypothesizes that infants from 14 months of age help others to minimize the differences between predicted actions and observations, that is, to minimize prediction errors, and implemented a computational model based on psychological studies and implemented it in real and simulated robots.
Proceedings ArticleDOI

Research on LatticeLSTM model based on data enhancement and self-attention mechanism

TL;DR: In this article , the authors used LatticeLSTM model and self-attention mechanism to improve the ability to understand Chinese semantics and build a data set in a special field for named entity recognition.
References
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Journal ArticleDOI

Backpropagation through time: what it does and how to do it

TL;DR: This paper first reviews basic backpropagation, a simple method which is now being widely used in areas like pattern recognition and fault diagnosis, and describes further extensions of this method, to deal with systems other than neural networks, systems involving simultaneous equations or true recurrent networks, and other practical issues which arise with this method.
Journal ArticleDOI

Understanding the Intentions of Others: Re-Enactment of Intended Acts by 18-Month-Old Children.

TL;DR: Eighteen-month-olds situate people within a psychological framework that differentiates between the surface behavior of people and a deeper level involving goals and intentions and showed that children could infer the adult's intended act by watching the failed attempts.
Journal ArticleDOI

Fourteen- through 18-month-old infants differentially imitate intentional and accidental actions

TL;DR: This paper explored infants' ability to discriminate between, and their tendency to reproduce, the accidental and intentional actions of others, and found that infants imitated almost twice as many of the adult's intentional actions as her accidental ones.
Journal ArticleDOI

Imitation of gestures in children is goal-directed.

TL;DR: The view that the motor program activated during imitation is organized by goals was investigated by asking pre-school children to imitate a set of hand gestures of varying complexity that were made by an experimenter sitting in front of them.
Journal ArticleDOI

Cognitive Developmental Robotics: A Survey

TL;DR: Cognitive developmental robotics aims to provide new understanding of how human's higher cognitive functions develop by means of a synthetic approach that developmentally constructs cognitive functions through interactions with the environment, including other agents.
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