Literature DB >> 26969919

How Evolution May Work Through Curiosity-Driven Developmental Process.

Pierre-Yves Oudeyer1, Linda B Smith2.   

Abstract

Infants' own activities create and actively select their learning experiences. Here we review recent models of embodied information seeking and curiosity-driven learning and show that these mechanisms have deep implications for development and evolution. We discuss how these mechanisms yield self-organized epigenesis with emergent ordered behavioral and cognitive developmental stages. We describe a robotic experiment that explored the hypothesis that progress in learning, in and for itself, generates intrinsic rewards: The robot learners probabilistically selected experiences according to their potential for reducing uncertainty. In these experiments, curiosity-driven learning led the robot learner to successively discover object affordances and vocal interaction with its peers. We explain how a learning curriculum adapted to the current constraints of the learning system automatically formed, constraining learning and shaping the developmental trajectory. The observed trajectories in the robot experiment share many properties with those in infant development, including a mixture of regularities and diversities in the developmental patterns. Finally, we argue that such emergent developmental structures can guide and constrain evolution, in particular with regard to the origins of language.
Copyright © 2016 Cognitive Science Society, Inc.

Entities:  

Keywords:  Curiosity; Development; Evolution; Infant active learning; Motor development; Origins of language; Robotic modelling; Self-organization; Speech development

Mesh:

Year:  2016        PMID: 26969919     DOI: 10.1111/tops.12196

Source DB:  PubMed          Journal:  Top Cogn Sci        ISSN: 1756-8757


  16 in total

Review 1.  The Developing Infant Creates a Curriculum for Statistical Learning.

Authors:  Linda B Smith; Swapnaa Jayaraman; Elizabeth Clerkin; Chen Yu
Journal:  Trends Cogn Sci       Date:  2018-03-05       Impact factor: 20.229

2.  Visual segmentation of complex naturalistic structures in an infant eye-tracking search task.

Authors:  Karola Schlegelmilch; Annie E Wertz
Journal:  PLoS One       Date:  2022-04-01       Impact factor: 3.240

3.  Parent-Child Joint Behaviors in Novel Object Play Create High-Quality Data for Word Learning.

Authors:  Chi-Hsin Chen; Derek M Houston; Chen Yu
Journal:  Child Dev       Date:  2021-08-31

4.  Sampling to learn words: Adults and children sample words that reduce referential ambiguity.

Authors:  Martin Zettersten; Jenny R Saffran
Journal:  Dev Sci       Date:  2020-12-07

5.  Latent learning, cognitive maps, and curiosity.

Authors:  Maya Zhe Wang; Benjamin Y Hayden
Journal:  Curr Opin Behav Sci       Date:  2020-07-17

6.  The Brain Circuits and Dynamics of Curiosity-Driven Behavior in Naturally Curious Marmosets.

Authors:  Xiaoguang Tian; Afonso C Silva; Cirong Liu
Journal:  Cereb Cortex       Date:  2021-07-29       Impact factor: 5.357

7.  Statistical language learning in infancy.

Authors:  Jenny R Saffran
Journal:  Child Dev Perspect       Date:  2020-01-19

8.  Visual Attention Preference for Intermediate Predictability in Young Children.

Authors:  Laura S Cubit; Rebecca Canale; Rebecca Handsman; Celeste Kidd; Loisa Bennetto
Journal:  Child Dev       Date:  2021-01-08

9.  The effects of task difficulty, novelty and the size of the search space on intrinsically motivated exploration.

Authors:  Adrien F Baranes; Pierre-Yves Oudeyer; Jacqueline Gottlieb
Journal:  Front Neurosci       Date:  2014-10-14       Impact factor: 4.677

10.  MCA-NMF: Multimodal Concept Acquisition with Non-Negative Matrix Factorization.

Authors:  Olivier Mangin; David Filliat; Louis Ten Bosch; Pierre-Yves Oudeyer
Journal:  PLoS One       Date:  2015-10-21       Impact factor: 3.240

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