Enactive artificial intelligence: Investigating the systemic organization of life and mind

By Tom Froese, Tom Ziemke. Artificial Intelligence, 2009

328 citations recorded by the source corpus.

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.

Subfields: Cognitive Neuroscience, Social Psychology

View Paper: https://www.semanticscholar.org/paper/144aef90608def9088b33436856d49e0b9872ee8

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Citations in the corpus

Evolving Plastic Neuromodulated Networks for Behavior Emergence of Autonomous Virtual Characters (2013, methodology): “This position is motivated by the Embodied (Anderson (2003)) and Enactive (Froese and Ziemke (2009)) approaches to AI, where intelligence is perceived as something that emerges from a close interaction among all the components involved in the cognitive phenomenon.”
Radicalizing Enactivism: Basic Minds without Content (2012, background): “…basic minds is only applicable to living beings: it does not matter how intelligent the behavior-‐based robot appears to be, nor does it matter, in direct contrast to a Millikanian theory of intentionality, whether its behavior has been selected by artificial evolution (Froese and Ziemke, 2009).”
Emergent vision system of autonomous virtual characters (2016, methodology): “The model just described is known as the computational paradigm for cognition [12].”
Sociality and the life–mind continuity thesis (2009, background): “However, since these notions have already been the target of much recent work (e.g. Di Paolo 2009; Thompson 2007; Froese and Ziemke 2009), here we only highlight some aspects.”