Maturationally-Constrained Competence-Based Intrinsically Motivated Learning - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2010

Maturationally-Constrained Competence-Based Intrinsically Motivated Learning

Abstract

This paper studies the coupling of intrinsic motiva- tion and physiological maturational constraints, and argues that both mechanisms may have complex bidirectional interactions allowing to actively control the growth of complexity in motor development. First, we introduce the self-adaptive goal generation algorithm (SAGG), instantiating an intrinsically motivated goal exploration mechanism for motor learning of inverse models. Then, we introduce a functional model of maturational con- straints inspired by the myelination process in humans, and show how it can be coupled with the SAGG algorithm, forming a new system called McSAGG. We then present experiments to evaluate qualitative properties of these systems when applied to learning a reaching skill with an arm with initially unknown kinematics.
Fichier principal
Vignette du fichier
BaranesOudeyerICDL10.pdf (817.44 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

inria-00541770 , version 1 (01-12-2010)

Identifiers

  • HAL Id : inria-00541770 , version 1

Cite

Adrien Baranes, Pierre-Yves Oudeyer. Maturationally-Constrained Competence-Based Intrinsically Motivated Learning. IEEE International Conference on Development and Learning (ICDL 2010), 2010, Ann Arbor, United States. ⟨inria-00541770⟩
180 View
270 Download

Share

Gmail Facebook Twitter LinkedIn More