The nature of cognition is being re-considered. Instead of emphasizing formal operations on abstract symbols, the new approach foregrounds the fact that cognition is, rather, a situated activity, and suggests that thinking beings ought therefore be considered first and foremost as acting beings. The essay reviews recent work in Embodied Cognition, provides a concise guide to its principles, attitudes and goals, and identifies the physical grounding project as its central research focus.

Different varieties of enactivism struggle to fill the empty throne after the long reign of representational cognitivism. And the notion of autonomy is one of the central claims under dispute within the different enactivist research programmes, des- pite the central role that it played on the early enactivist founda- tions. It is the very autonomy of enactivism itself what is at stake here, if it doesn’t want to be integrated back into a reformed ver- sion of representational cognitivism or subsumed under new forms of behaviourism. In this work I will show why autonomy is a necessary component of the enactive programme, I shall cla- rify some foundational misunderstandings or conceptual obstacles that have made autonomy a difficult notion to assume for some sensorimotor enactive approaches and, finally, I will propose to introduce autonomy back at the roots of enactivism through the notion of habit and sensorimotor agency. 1

There are many varieties of epistemological and cognitive constructivism. They have in common an appreciation of the failures of centuries of attempts to realize a correspondence notion of truth and representation, and they all propose some constructivist programme as an alternative. The programmatic proposals, however, can differ greatly. Some contemporary constructivisms that are being vigorously advocated propose a social form of idealism with a consequent relativism. Such proposals risk giving constructivism a bad name. The main burden of this article is to show that such an idealism and relativism is not forced by constructivism, but, instead, is the result of an additional and questionable presupposition. Constructivism per se is a strong epistemological position that is fully compatible with realism.

Key words: cognition, constructivism, correspondence, encoding, epistemology, idealism, realism, relativism, representation

Autonomy is modeled in terms of the property of certain far-from-equilibrium open systems to contribute toward maintaining themselves in their far-from-equilibrium conditions. Such contributions in self-maintenant systems, in turn, constitute the emergence of normative function. The intrinsic thermodynamic asymmetry between equilibrium and far-from-equilibrium processes yields the intrinsic normative asymmetry between function and dysfunction. Standard etiological models of function render function as causally epiphenomenal, while this model is of the emergence of causally efficacious function. Recursive self-maintenance – the meta-property of maintaining the property of being self-maintenant across variations in environment – yields the emergence of representation. This model of representation satisfies multiple criteria that standard approaches – such as symbolic or connectionist, or those of Fodor, Dretske, or Millikan – cannot.

The main contribution of this paper is a naturalized account of the phenomenon of computation. The key idea for the development of this account is the identification of the notion of syntactical processing (or information processing) with the dynamical evolution of a constrained physical process, based on the observation that both evolve according to an arbitrary set of rules. This identification, in turn, revealed that, from the physical point of view, computation could be understood in terms of the operation of a component subdivided into two parts, (a) the constrained process and (b) the constraints that control its dynamics, where the interactions with the rest of the system are mediated by configurational changes of the constrained process. The immediate consequence of this analysis is the observation that this notion of computation can be readily integrated into the enactive paradigm of cognition.

Key words: enaction, computation, syntax, arbitrariness, computation, varela, organism, searle.

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporate – everything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments.

Mike Anderson has given us a thoughtful and useful field guide: Not in the genre of a bird-watcher’s guide which is carried in the field and which contains detailed descriptions of possible sightings, but in the sense of a guide to a field (in this case embodied cognition) which aims to identify that field’s general principles and properties. I’d like to make some comments that will hopefully complement Anderson’s work, highlighting points of agreement and disagreement between his view of the field and my own, and acting as a devil’s advocate in places where further discussion seems to be required. Given the venue for this guide, we can safely restrict the discussion to embodied artificial intelligence (EAI), even if such work draws on notions of embodied cognition from the fields of philosophy, psychology and linguistics. In particular, I’ll restrict my discussion to the impact that embodiment can have on the task of creating artificial intelligent agents, either as technological ends in themselves, or as means to understanding natural intelligent systems, or both.

This paper outlines an interactivist-constructivist theory of autonomy as the basic organisational form of life, and the role we see it playing in a theory of embodied cognition. We distinguish our concept of autonomy from autopoiesis, which does not emphasise interaction and openness. We then present the basic conceptual framework of the I-C approach to intelligence, including an account of directed processes, dynamical anticipation, normative evaluation, and selfdirectedness as the basis of intelligence and learning, and use this to briefly reflect on other contemporary dynamical systems approaches.

Artificial Intelligence researchers and cognitive scientists commonly believe that thinking involves manipulating representations. Thinking involves search, inference, and making choices. This is how we model reasoning and what goes on in the brain is similar. Winograd and Flores present a radically different view, claiming that our knowledge is not represented in the brain at all, but rather consists of an unformalized shared background, from which we articulate representations in order to cope with new situations. In contrast, computer programs contain only pre-selected objects and properties, and there is no basis for moving beyond this initial formalization when breakdown occurs. Winograd and Flores provide convincing arguments with examples familiar to most artificial intelligence researchers. However, they significantly understate the role of representation in mediating intelligent behavior, specifically in the process of reflection, when representations are generated prior to physical action. Furthermore, they do not consider the practical benefits of expert systems and the extent of what can be accomplished. Nevertheless, the book is crisp and stimulating, and should make artificial intelligence researchers more cautious about what they are doing, more aware of the nature of formalization, and more open to alternative views.