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        How mobile robots can self-organise a vocabulary

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        Author(s)
        Vogt, Paul
        Collection
        Knowledge Unlatched (KU)
        Language
        English
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        Abstract
        One of the hardest problems in science is the symbol grounding problem, a question that has intrigued philosophers and linguists for more than a century. With the rise of artificial intelligence, the question has become very actual, especially within the field of robotics. The problem is that an agent, be it a robot or a human, perceives the world in analogue signals. Yet humans have the ability to categorise the world in symbols that they, for instance, may use for language. This book presents a series of experiments in which two robots try to solve the symbol grounding problem. The experiments are based on the language game paradigm, and involve real mobile robots that are able to develop a grounded lexicon about the objects that they can detect in their world. Crucially, neither the lexicon nor the ontology of the robots has been preprogrammed, so the experiments demonstrate how a population of embodied language users can develop their own vocabularies from scratch.
        URI
        http://library.oapen.org/handle/20.500.12657/32838
        Keywords
        language in robots; artificial intelligence; Feature extraction; Feature vector; Joint attention; Lexicon; Reference; Symbol grounding problem; Talking Heads
        DOI
        10.26530/OAPEN_603358
        ISBN
        9783946234012
        OCN
        945783174
        Publisher
        Language Science Press
        Publisher website
        https://langsci-press.org/
        Publication date and place
        2015
        Grantor
        • Knowledge Unlatched
        Series
        Computational Models of Language Evolution, 2
        Classification
        Linguistics
        Computing and Information Technology
        Pages
        270
        Public remark
        Relevant Wikipedia pages: Feature extraction - https://en.wikipedia.org/wiki/Feature_extraction; Feature vector - https://en.wikipedia.org/wiki/Feature_vector; Joint attention - https://en.wikipedia.org/wiki/Joint_attention; Language game - https://en.wikipedia.org/wiki/Language_game; Lexicon - https://en.wikipedia.org/wiki/Lexicon; Reference - https://en.wikipedia.org/wiki/Reference; Robot - https://en.wikipedia.org/wiki/Robot; Symbol grounding problem - https://en.wikipedia.org/wiki/Symbol_grounding_problem; Talking Heads - https://en.wikipedia.org/wiki/Talking_Heads
        Rights
        https://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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