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A Demonstration of the Efficiency of Developmental Learning



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A Demonstration of the Efficiency of Developmental Learning Marek W Doniec Ganghua Sun Brian Scassellati Department of Computer Science Yale University New Haven Connecticut 06511 U S A marek doniec ganghua sun brian scassellati yale edu Abstract Previous research has suggested that developmental learning can make the learning of advanced sensorimotor and cognitive skills possible In this paper we demonstrate that developmental learning based on skill progression is also more efficient than traditional divide and conquer methods Using a model based on the skills of reaching and pointing to visual targets we demonstrate an implementation for a humanoid robot that is more efficient at learning joint attention skills than other published methods This efficiency results from 1 a structured set of learning tasks that progresses from low dimensional to high dimensional problems and 2 a greater exploitation of the learning environment that does not follow from the completely task based decomposition that divide and conquer provides I I NTRODUCTION The word development has been used in computer science with many different meanings It can mean maturation of sensory and motor capacities such as improvement of visual acuity and increase of muscle strength It is often used as a substitute for learning of specific skills such as reaching or walking In this paper we reserve the word development to mean the acquisition of a progression of skills Although there is a great deal of variability among individual infants typically skills in different domains are mastered in an orderly fashion Infants usually learn to sit and crawl before they start to walk Single words are uttered before syntax and grammar are mastered It has been suggested that following a developmental progression of skills might enable a robot to achieve the intelligence or capabilities of an infant 1 2 Most applications of developmental learning in robotics focus on the learning of individual skills Metta et al



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