Evidence map›Paper›PMID 29914999›Full record

ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2018

A review of abstract concept learning in embodied agents and robots.

Angelo Cangelosi, Francesca Stramandinoli

Abstract readReview
In one paragraph

Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Review
  3. Editorial concepts in interaction: social engagement and inner experiences.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Varieties of abstract concepts: development, use and representation in the brain.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018
    Article
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

2 authors.

Angelo CangelosiCentre for Robotics and Neural Systems, Plymouth University, Plymouth PL4 8AA, UK a.cangelosi@plymouth.ac.uk.ORCID 0000-0002-4709-2243
Francesca StramandinoliiCub Facility Department, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genoa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper reviews computational modelling approaches to the learning of abstract concepts and words in embodied agents such as humanoid robots. This will include a discussion of the learning of abstract words such as 'use' and 'make' in humanoid robot experiments, and the acquisition of numerical concepts via gesture and finger counting strategies. The current approaches share a strong emphasis on embodied cognition aspects for the grounding of abstract concepts, and a continuum, rather than dichotomy, view of concrete/abstract concepts differences.This article is part of the theme issue 'Varieties of abstract concepts: development, use and representation in the brain'.

Indexed as

Concept FormationLearningRoboticsSpeechHumansModels, Psychologicalabstract concept learningcognitive roboticsembodied cognitionnumerical conceptssymbol grounding

Identifiers

PMID29914999
PMCPMC6015819

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.