creators_name: Chen, Yi
creators_name: Weng, Juyang
editors_name: Berthouze, Luc
editors_name: Kozima, Hideki
editors_name: Prince, Christopher G.
editors_name: Sandini, Giulio
editors_name: Stojanov, Georgi
editors_name: Metta, Giorgio
editors_name: Balkenius, Christian
type: confpaper
datestamp: 2005-04-14
lastmod: 2011-03-11 08:55:50
metadata_visibility: show
title: Developmental Learning: A Case Study in Understanding “Object Permanence”
ispublished: pub
subjects: comp-sci-mach-learn
subjects: comp-sci-art-intel
subjects: comp-sci-robot
full_text_status: public
keywords: developmental learning, object permanence, robot, robotic perceptual development, computational model
abstract: The concepts of muddy environment and muddy tasks set the ground for us to understand the essence of intelligence, both artificial and natural, which further motivates the need of Developmental Learning for machines. In this paper, a biologically inspired computational model is proposed to study one of the fundamental and controversial issues in cognitive science – “Object Permanence.” This model is implemented on a robot, which enables us to examine the robot’s behavior based on perceptual development through realtime experiences. Our experimental result shows consistency with prior researches on human infants, which not only sheds light on the highly controversial issue of object permanence, but also demonstrates how biologically inspired developmental models can potentially develop intelligent machines and verify computationalmodeling that has been established in cognitive science.
date: 2004
date_type: published
volume: 117
publisher: Lund University Cognitive Studies
pagerange: 35-42
refereed: TRUE
citation:   Chen, Yi and Weng, Juyang  (2004) Developmental Learning: A Case Study in Understanding “Object Permanence”.  [Conference Paper]     
document_url: http://cogprints.org/4057/1/chen.pdf