Conceptual and Methodological Problems with Comparative Work on Artificial Language Learning
Several theoretical proposals for the evolution of language have sparked a renewed search for comparative data on human and non-human animal computational capacities. However, conceptual confusions still hinder the field, leading to experimental evidence that fails to test for comparable human compe...
Main Authors: | , , |
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Format: | Article |
Language: | English |
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PsychOpen GOLD/ Leibniz Institute for Psychology
2014-04-01
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Series: | Biolinguistics |
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Online Access: | https://doi.org/10.5964/bioling.8995 |
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author | Jeffrey Watumull Marc D. Hauser Robert C. Berwick |
author_facet | Jeffrey Watumull Marc D. Hauser Robert C. Berwick |
author_sort | Jeffrey Watumull |
collection | DOAJ |
description | Several theoretical proposals for the evolution of language have sparked a renewed search for comparative data on human and non-human animal computational capacities. However, conceptual confusions still hinder the field, leading to experimental evidence that fails to test for comparable human competences. Here we focus on two conceptual and methodological challenges that affect the field generally: 1) properly characterizing the computational features of the faculty of language in the narrow sense; 2) defining and probing for human language-like computations via artificial language learning experiments in non-human animals. Our intent is to be critical in the service of clarity, in what we agree is an important approach to understanding how language evolved. |
first_indexed | 2024-03-08T09:25:45Z |
format | Article |
id | doaj.art-2c8f9a7d78004744b6139f944fe007d7 |
institution | Directory Open Access Journal |
issn | 1450-3417 |
language | English |
last_indexed | 2024-03-08T09:25:45Z |
publishDate | 2014-04-01 |
publisher | PsychOpen GOLD/ Leibniz Institute for Psychology |
record_format | Article |
series | Biolinguistics |
spelling | doaj.art-2c8f9a7d78004744b6139f944fe007d72024-01-31T09:42:20ZengPsychOpen GOLD/ Leibniz Institute for PsychologyBiolinguistics1450-34172014-04-01812012910.5964/bioling.89958995Conceptual and Methodological Problems with Comparative Work on Artificial Language LearningJeffrey Watumull0Marc D. HauserRobert C. BerwickUniversity of CambridgeSeveral theoretical proposals for the evolution of language have sparked a renewed search for comparative data on human and non-human animal computational capacities. However, conceptual confusions still hinder the field, leading to experimental evidence that fails to test for comparable human competences. Here we focus on two conceptual and methodological challenges that affect the field generally: 1) properly characterizing the computational features of the faculty of language in the narrow sense; 2) defining and probing for human language-like computations via artificial language learning experiments in non-human animals. Our intent is to be critical in the service of clarity, in what we agree is an important approach to understanding how language evolved.https://doi.org/10.5964/bioling.8995artificial language learningfaculty of language in the narrow senserecursion |
spellingShingle | Jeffrey Watumull Marc D. Hauser Robert C. Berwick Conceptual and Methodological Problems with Comparative Work on Artificial Language Learning Biolinguistics artificial language learning faculty of language in the narrow sense recursion |
title | Conceptual and Methodological Problems with Comparative Work on Artificial Language Learning |
title_full | Conceptual and Methodological Problems with Comparative Work on Artificial Language Learning |
title_fullStr | Conceptual and Methodological Problems with Comparative Work on Artificial Language Learning |
title_full_unstemmed | Conceptual and Methodological Problems with Comparative Work on Artificial Language Learning |
title_short | Conceptual and Methodological Problems with Comparative Work on Artificial Language Learning |
title_sort | conceptual and methodological problems with comparative work on artificial language learning |
topic | artificial language learning faculty of language in the narrow sense recursion |
url | https://doi.org/10.5964/bioling.8995 |
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