Enactive artificial intelligence: Investigating the systemic organization of life and mind
2009 (English)In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 173, no 3-4, p. 466-500Article in journal (Refereed) Published
Abstract [en]
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.
Place, publisher, year, edition, pages
Elsevier, 2009. Vol. 173, no 3-4, p. 466-500
Keywords [en]
Embodied, Situated, Enactive, Cognitive science, Agency, Autonomy, Intentionality, Design principles, Natural cognition, Modeling
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-2911DOI: 10.1016/j.artint.2008.12.001ISI: 000263763900003Scopus ID: 2-s2.0-58549117703OAI: oai:DiVA.org:his-2911DiVA, id: diva2:209578
2009-03-252009-03-252018-01-13Bibliographically approved