Embodying Cognition: A Morphological Perspective

Embodying Cognition: A Morphological Perspective

David Casacuberta (Universitat Autonoma de Barcelona, Spain), Saray Ayala (Universitat Autònoma de Barcelona, Spain) and Jordi Vallverdú (Universitat Autònoma de Barcelona, Spain)
Copyright: © 2012 |Pages: 21
DOI: 10.4018/978-1-60960-818-7.ch707
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Abstract

After several decades of success in different areas and numerous effective applications, algorithmic Artificial Intelligence has revealed its limitations. If in our quest for artificial intelligence we want to understand natural forms of intelligence, we need to shift/move from platform-free algorithms to embodied and embedded agents. Under the embodied perspective, intelligence is not so much a matter of algorithms, but of the continuous interactions of an embodied agent with the real world. In this paper we adhere to a specific reading of the embodied view usually known as enactivism, to argue that 1) It is a more reasonable model of how the mind really works; 2) It has both theoretical and empirical benefits for Artificial Intelligence and 3) Can be easily implemented in simple robotic sets like Lego Mindstorms (TM). In particular, we will explore the computational role that morphology can play in artificial systems. We will illustrate our ideas presenting several Lego Mindstorms robots where morphology is critical for the robot’s behaviour.
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1. From Symbols To Bodies

Artificial Intelligence (AI) can be approached just with an engineering frame of mind, looking for algorithms that work and are able to solve a problem. However, one can settle to a philosophical one too, and consider AI a conceptual tool to get better insight on what the mind is and how it works. Within this frame of mind, just solving problems is not enough: we want our theory to have, to a certain degree, psychological reality. We want our model to embed some of the earthly properties that human minds have. Currently, discussion is mainly around three main models concerning what the mind is: symbolic cognitivism, connectionism and the embodied mind. In this paper we adhere to the third model; in particular, to a special branch usually known as enactivism, to argue that (1) It is a more reasonable model of how the mind really works; (2) It has both theoretical and empirical benefits for AI; and (3) Can be easily implemented in simple robotic sets like Lego Mindstorms (TM).

Much has already been written about the differences between these three mind models, and which is the superior one. To our understanding, despite their success in creating models on subjects like mathematical reasoning, face recognition, visual perception or even creating artworks, both the cognitivist and the connectionist approaches have one major flaw which is of considerable philosophical importance: they cannot produce a credible account of the relationship between mind and world. Being local symbolic representations or distributed subsymbolic representations, both models are based on an abstract reconstruction of a specific domain of the physical world, both the selection and the way representations are connected to real life events and objects has been articulated beforehand by the cognitive system (Thompson 2007). Connectionism tries to generate a more plausible description of the mind, trying to better capture its neurological basis. This leads to a more dynamic account of representations: instead of being something stable, they are distributed along the whole system as well as self-organised, having certain co-variation with the environment. However, both symbolic cognitivism and connectionism consider the world and the mind as two completely different entities, with a very much regulated protocol of interaction.

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