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Enactive artificial...
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Froese, TomCentre for Computational Neuroscience and Robotics (CCNR), Centre for Research in Cognitive Science (COGS), University of Sussex, Brighton, United Kingdom
(author)
Enactive artificial intelligence : Investigating the systemic organization of life and mind
- Article/chapterEnglish2009
Publisher, publication year, extent ...
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Elsevier,2009
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printrdacarrier
Numbers
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LIBRIS-ID:oai:DiVA.org:his-2911
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https://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-2911URI
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https://doi.org/10.1016/j.artint.2008.12.001DOI
Supplementary language notes
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Language:English
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Summary in:English
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Classification
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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The embodied and situated approach to artificial intelligence (AI) has matured and become a viable alternative to traditional computationalist approaches with respect to the practical goal of building artificial agents, which can behave in a robust and flexible manner under changing real-world conditions. Nevertheless, some concerns have recently been raised with regard to the sufficiency of current embodied AI for advancing our scientific understanding of intentional agency. While from an engineering or computer science perspective this limitation might not be relevant, it is of course highly relevant for AI researchers striving to build accurate models of natural cognition. We argue that the biological foundations of enactive cognitive science can provide the conceptual tools that are needed to diagnose more clearly the shortcomings of current embodied AI. In particular, taking an enactive perspective points to the need for AI to take seriously the organismic roots of autonomous agency and sense-making. We identify two necessary systemic requirements, namely constitutive autonomy and adaptivity, which lead us to introduce two design principles of enactive AI. It is argued that the development of such enactive AI poses a significant challenge to current methodologies. However, it also provides a promising way of eventually overcoming the current limitations of embodied AI, especially in terms of providing fuller models of natural embodied cognition. Finally, some practical implications and examples of the two design principles of enactive AI are also discussed.
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Ziemke, TomHögskolan i Skövde,Institutionen för kommunikation och information,Forskningscentrum för Informationsteknologi(Swepub:his)ziet
(author)
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Centre for Computational Neuroscience and Robotics (CCNR), Centre for Research in Cognitive Science (COGS), University of Sussex, Brighton, United KingdomInstitutionen för kommunikation och information
(creator_code:org_t)
Related titles
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In:Artificial Intelligence: Elsevier173:3-4, s. 466-5000004-37021872-7921
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