Evidence map›Paper›PMID 30018547›Full record

ArticleFrontiers in neurorobotics2018

Know Your Body Through Intrinsic Goals.

Francesco Mannella, Vieri G Santucci, Eszter Somogyi, Lisa Jacquey, Kevin J O'Regan, Gianluca Baldassarre

Abstract read
In one paragraph

Article in Frontiers in neurorobotics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Kick-starting concept formation with intrinsically motivated learning: the grounding by competence acquisition hypothesis.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
  2. Review
  3. Prerequisites for an Artificial Self.Frontiers in neurorobotics · 2020
    Review
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Francesco MannellaInstitute of Cognitive Sciences and Technologies, National Research Council - CNR, Rome, Italy.
Vieri G SantucciInstitute of Cognitive Sciences and Technologies, National Research Council - CNR, Rome, Italy.
Eszter SomogyiLaboratoire Psychologie de la Perception (UMR 8242), Paris Descartes - CPSC, Paris, France.
Lisa JacqueyLaboratoire Psychologie de la Perception (UMR 8242), Paris Descartes - CPSC, Paris, France.
Kevin J O'ReganLaboratoire Psychologie de la Perception (UMR 8242), Paris Descartes - CPSC, Paris, France.
Gianluca BaldassarreInstitute of Cognitive Sciences and Technologies, National Research Council - CNR, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

bodydevelopmental psychologydevelopmental roboticsgoalsintrinsic motivations

Identifiers

PMID30018547
PMCPMC6037791

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.