Online research in philosophy

1. The Situation in Cognition 2. Situated Cognition: A Potted Recent History 3. Extensions in Biology, Computation, and Cognition 4. Articulating the Idea of Cognitive Extension 5. Are Some Resources Intrinsically Non-Cognitive? 6. Is Cognition Extended or Only Embedded? 7. Letting Nature Take Its Course.

In order to investigate cognition fundamental assumptions must be made about what, in general terms, it is. In cognitive science it is usually assumed that cognition is computational and representational. There have been well known disputes over these assumptions, with rival claims that cognition is dynamical, situated and embodied. In this paper I emphasize the relations between cognition and control. I present a model of cognition that makes the claim that it is a form of high-order control, and I argue that viewing cognition as high-order control could be a useful framework assumption for cognitive science. Cognition has many aspects and different concepts can emphasize different aspects of it. Computational and representational assumptions have been very productive, and dynamical and embodied assumptions have also been productive, though to a much lesser extent so far. Control, however, has received insufficient attention in cognition science. The model I propose is based on a point that few will dispute, namely that control of behavior is the ultimate function of cognition. Bringing this to the foreground can be productive by highlighting the ways in which cognition is structured in relation to this control function. If this perspective is valuable it will be because the control function has a highly structuring effect on cognition. As a result a control-based perspective will predict many features of cognition and yield a coherent, integrated picture.

This book is a definitive reference source for the growing, increasingly more important, and interdisciplinary field of computational cognitive modeling, that is, computational psychology. It combines breadth of coverage with definitive statements by leading scientists in this field. Research in computational cognitive modeling explores the essence of cognition through developing detailed, process-based understanding by specifying computational mechanisms, structures, and processes. Computational models provide both conceptual clarity and precision at the same time. This book substantiates this approach through overviews and many examples.

Extended cognition is the view that some cognitive processes extend beyond the brain. One prominent strategy of arguing against extended cognition is to offer necessary conditions on cognition and argue that the proposed extended processes fail to satisfy these conditions (Adams and Aizawa, 2008; Rupert, 2010; Weiskopf, 2008). I argue that this strategy is misguided and fails to refute extended cognition. I suggest a better way to evaluate the case for extended cognition that should be acceptable to all parties, captures the intuitiveness of previous objections, and avoids the problems with the strategy of offering necessary conditions on cognition. I conclude that extended cognition theorists have failed to establish the truth of extended cognition.

The distinction between such differing approaches to cognition as connectionism and rule-based models is paralleled by a distinction between two basic modes of cognition postulated in the so-called dual-process theories. Integrating these theories with insights from hybrid systems might help solve the dilemma of combining the demands of evolutionary plausibility and computational universality. No single approach alone can achieve this.

Cognition is thinking; it feels like something to think, and only those who can feel can think. There are also things that thinkers can do. We know neither how thinkers can think nor how they are able do what they can do. We are waiting for cognitive science to discover how. Cognitive science does this by testing hypotheses about what processes can generate what doing (“know-how”) This is called the Turing Test. It cannot test whether a process can generate feeling, hence thinking -- only whether it can generate doing. The processes that generate thinking and know-how are “distributed” within the heads of thinkers, but not across thinkers’ heads. Hence there is no such thing as distributed cognition, only collaborative cognition. Email and the Web have spawned a new form of collaborative cognition that draws upon individual brains’ real-time interactive potential in ways that were not possible in oral, written or print interactions.

This article presents an approach to understanding human spatial competence that focuses on the representations and processes of spatial cognition and how they are integrated with cognition more generally. The foundational theoretical argument for this research is that spatial information processing is central to cognition more generally, in the sense that it is brought to bear ubiquitously to improve the adaptivity and effectiveness of perception, cognitive processing, and motor action. We describe research spanning multiple levels of complexity to understand both the detailed mechanisms of spatial cognition, and how they are utilized in complex, naturalistic tasks. In the process, we discuss the critical role of cognitive architectures in developing a consistent account that spans this breadth, and we note some areas in which the current version of a popular architecture, ACT-R, may need to be augmented. Finally, we suggest a framework for understanding the representations and processes of spatial competence and their role in human cognition generally.

Embodied Cognition is an approach to cognition that departs from traditional cognitive science in its reluctance to conceive of cognition as computational and in its emphasis on the significance of an organism’s body in how and what the organism thinks. Three lines of embodied cognition research are described and some thoughts on the future of embodied cognition offered.

In this paper, I discuss connections between self-directedness, integration and higher cognition. I present a model of self-directedness as a basis for approaching higher cognition from a situated cognition perspective. According to this model increases in sensorimotor complexity create pressure for integrative higher order control and learning processes for acquiring information about the context in which action occurs. This generates complex articulated abstractive information processing, which forms the major basis for higher cognition. I present evidence that indicates that the same integrative characteristics found in lower cognitive process such as motor adaptation are present in a range of higher cognitive process, including conceptual learning. This account helps explain situated cognition phenomena in humans because the integrative processes by which the brain adapts to control interaction are relatively agnostic concerning the source of the structure participating in the process. Thus, from the perspective of the motor control system using a tool is not fundamentally different to simply controlling an arm.