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Journal ArticleDOI

Cognitive Developmental Robotics: A Survey

TLDR
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.
Abstract
Cognitive developmental robotics (CDR) aims to provide new understanding of how human's higher cognitive functions develop by means of a synthetic approach that developmentally constructs cognitive functions. The core idea of CDR is ldquophysical embodimentrdquo that enables information structuring through interactions with the environment, including other agents. The idea is shaped based on the hypothesized development model of human cognitive functions from body representation to social behavior. Along with the model, studies of CDR and related works are introduced, and discussion on the model and future issues are argued.

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Neuroscience 細胞死:最近の知見

廣瀬雄一
TL;DR: In this paper, the authors describe a scenario where a group of people are attempting to find a solution to the problem of "finding the needle in a haystack" in the environment.
Journal ArticleDOI

Building machines that learn and think like people.

TL;DR: In this article, a review of recent progress in cognitive science suggests that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it.
Journal ArticleDOI

Information-seeking, curiosity, and attention: computational and neural mechanisms

TL;DR: Eye movements reflect visual information searching in multiple conditions and are amenable for cellular-level investigations, which suggests that the oculomotor system is an excellent model system for understanding information-sampling mechanisms.
Journal ArticleDOI

Active learning of inverse models with intrinsically motivated goal exploration in robots

TL;DR: The Self-Adaptive Goal Generation Robust Intelligent Adaptive Curiosity (SAGG-RIAC) architecture is introduced as an intrinsically motivated goal exploration mechanism which allows active learning of inverse models in high-dimensional redundant robots.
Journal ArticleDOI

The challenges ahead for bio-inspired 'soft' robotics

TL;DR: Soft materials may enable the automation of tasks beyond the capacities of current robotic technology.
References
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Journal ArticleDOI

Development of structure and function in the infant brain: implications for cognition, language and social behaviour.

TL;DR: An overview of four domains that have been studied using techniques amenable to elucidating the brain/behaviour interface: language, face processing, object permanence, and joint attention is provided, with particular emphasis on studies focusing on early development.
Journal ArticleDOI

Android science: conscious and subconscious recognition

TL;DR: The framework of android science is proposed, the androids developed are introduced, and conscious and subconscious human recognition of these androIDS are discussed as a fundamental issue for android science.
Journal ArticleDOI

A Neurolinguistic Model of Grammatical Construction Processing

TL;DR: The objective of the current research is to outline a functional description of grammatical construction processing based on principles of psycholinguistics, develop a model of how these functions can be implemented in human neurophysiology, and demonstrate the feasibility of the resulting model in processing languages of typologically diverse natures, that is, English, French, and Japanese.
Journal ArticleDOI

Overview of the Lucy Project : Dynamic Stabilization of a Biped Powered by Pneumatic Artificial Muscles

TL;DR: An overview of the Lucy project, which is special is that the biped is not actuated with the classical electrical drives, but with pleated pneumatic artificial muscles, to reduce the energy consumption by combining active trajectory control with the exploitation of the natural dynamics.
Journal ArticleDOI

Online learning of the body schema

TL;DR: An algorithm enabling a humanoid robot to visually learn its body schema, knowing only the number of degrees of freedom in each limb is presented, illustrating how subjective space representation can develop as a result of sensorimotor contingencies.
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