Know Your Body Through Intrinsic Goals

The first “object” that newborn children play with is their own body. This activity allows them to autonomously form a sensorimotor map of their own body and a repertoire of actions supporting future cognitive and motor development. Here we propose the theoretical hypothesis, operationalized as a co...

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Main Authors: Francesco Mannella, Vieri G. Santucci, Eszter Somogyi, Lisa Jacquey, Kevin J. O'Regan, Gianluca Baldassarre
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-07-01
Series:Frontiers in Neurorobotics
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fnbot.2018.00030/full
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spelling doaj-42bc369d3732472badb89624bc7c4f352020-11-24T21:58:16ZengFrontiers Media S.A.Frontiers in Neurorobotics1662-52182018-07-011210.3389/fnbot.2018.00030336300Know Your Body Through Intrinsic GoalsFrancesco Mannella0Vieri G. Santucci1Eszter Somogyi2Lisa Jacquey3Kevin J. O'Regan4Gianluca Baldassarre5Institute of Cognitive Sciences and Technologies, National Research Council - CNR, Rome, ItalyInstitute of Cognitive Sciences and Technologies, National Research Council - CNR, Rome, ItalyLaboratoire Psychologie de la Perception (UMR 8242), Paris Descartes - CPSC, Paris, FranceLaboratoire Psychologie de la Perception (UMR 8242), Paris Descartes - CPSC, Paris, FranceLaboratoire Psychologie de la Perception (UMR 8242), Paris Descartes - CPSC, Paris, FranceInstitute of Cognitive Sciences and Technologies, National Research Council - CNR, Rome, ItalyThe first “object” that newborn children play with is their own body. This activity allows them to autonomously form a sensorimotor map of their own body and a repertoire of actions supporting future cognitive and motor development. Here we propose the theoretical hypothesis, operationalized as a computational model, that this acquisition of body knowledge is not guided by random motor-babbling, but rather by autonomously generated goals formed on the basis of intrinsic motivations. Motor exploration leads the agent to discover and form representations of the possible sensory events it can cause with its own actions. When the agent realizes the possibility of improving the competence to re-activate those representations, it is intrinsically motivated to select and pursue them as goals. The model is based on four components: (1) a self-organizing neural network, modulated by competence-based intrinsic motivations, that acquires abstract representations of experienced sensory (touch) changes; (2) a selector that selects the goal to pursue, and the motor resources to train to pursue it, on the basis of competence improvement; (3) an echo-state neural network that controls and learns, through goal-accomplishment and competence, the agent's motor skills; (4) a predictor of the accomplishment of the selected goals generating the competence-based intrinsic motivation signals. The model is tested as the controller of a simulated simple planar robot composed of a torso and two kinematic 3-DoF 2D arms. The robot explores its body covered by touch sensors by moving its arms. The results, which might be used to guide future empirical experiments, show how the system converges to goals and motor skills allowing it to touch the different parts of own body and how the morphology of the body affects the formed goals. The convergence is strongly dependent on competence-based intrinsic motivations affecting not only skill learning and the selection of formed goals, but also the formation of the goal representations themselves.https://www.frontiersin.org/article/10.3389/fnbot.2018.00030/fulldevelopmental roboticsdevelopmental psychologyintrinsic motivationsgoalsbody
collection DOAJ
language English
format Article
sources DOAJ
author Francesco Mannella
Vieri G. Santucci
Eszter Somogyi
Lisa Jacquey
Kevin J. O'Regan
Gianluca Baldassarre
spellingShingle Francesco Mannella
Vieri G. Santucci
Eszter Somogyi
Lisa Jacquey
Kevin J. O'Regan
Gianluca Baldassarre
Know Your Body Through Intrinsic Goals
Frontiers in Neurorobotics
developmental robotics
developmental psychology
intrinsic motivations
goals
body
author_facet Francesco Mannella
Vieri G. Santucci
Eszter Somogyi
Lisa Jacquey
Kevin J. O'Regan
Gianluca Baldassarre
author_sort Francesco Mannella
title Know Your Body Through Intrinsic Goals
title_short Know Your Body Through Intrinsic Goals
title_full Know Your Body Through Intrinsic Goals
title_fullStr Know Your Body Through Intrinsic Goals
title_full_unstemmed Know Your Body Through Intrinsic Goals
title_sort know your body through intrinsic goals
publisher Frontiers Media S.A.
series Frontiers in Neurorobotics
issn 1662-5218
publishDate 2018-07-01
description The first “object” that newborn children play with is their own body. This activity allows them to autonomously form a sensorimotor map of their own body and a repertoire of actions supporting future cognitive and motor development. Here we propose the theoretical hypothesis, operationalized as a computational model, that this acquisition of body knowledge is not guided by random motor-babbling, but rather by autonomously generated goals formed on the basis of intrinsic motivations. Motor exploration leads the agent to discover and form representations of the possible sensory events it can cause with its own actions. When the agent realizes the possibility of improving the competence to re-activate those representations, it is intrinsically motivated to select and pursue them as goals. The model is based on four components: (1) a self-organizing neural network, modulated by competence-based intrinsic motivations, that acquires abstract representations of experienced sensory (touch) changes; (2) a selector that selects the goal to pursue, and the motor resources to train to pursue it, on the basis of competence improvement; (3) an echo-state neural network that controls and learns, through goal-accomplishment and competence, the agent's motor skills; (4) a predictor of the accomplishment of the selected goals generating the competence-based intrinsic motivation signals. The model is tested as the controller of a simulated simple planar robot composed of a torso and two kinematic 3-DoF 2D arms. The robot explores its body covered by touch sensors by moving its arms. The results, which might be used to guide future empirical experiments, show how the system converges to goals and motor skills allowing it to touch the different parts of own body and how the morphology of the body affects the formed goals. The convergence is strongly dependent on competence-based intrinsic motivations affecting not only skill learning and the selection of formed goals, but also the formation of the goal representations themselves.
topic developmental robotics
developmental psychology
intrinsic motivations
goals
body
url https://www.frontiersin.org/article/10.3389/fnbot.2018.00030/full
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