Wayne David Christensen

This paper outlines an original interactivist-constructivist approach to modelling intelligence and learning as a dynamical embodied form of adaptiveness and explores some applications of I-C to understanding the way cognitive learning is realized in the brain. Two key ideas for conceptualizing intelligence within this framework are developed. These are: intelligence is centrally concerned with the capacity for coherent, context-sensitive, self-directed management of interaction; and the primary model for cognitive learning is anticipative skill construction. Self-directedness is a capacity for integrative process modulation which allows a system to "steer" itself through its world by anticipatively matching its own viability requirements to interaction with its environment. Because the adaptive interaction processes required of intelligent systems are too complex for effective action to be prespecified learning is an important component of intelligence. A model of self-directed anticipative learning is formulated based on interactive skill construction, and argued to constitute a central constructivist process involved in cognitive development. SDAL illuminates the capacity of intelligent learners to start with the vague, poorly defined problems typically posed in realistic learning situations and progressively refine them, transforming them into problems with sufficient structure to guide the construction of a solution. Finally, some of the implications of I-C for modelling of the neuronal basis of intelligence and learning are explored; in particular, Quartz and Sejnowski's recent neural constructivism paradigm, enriched by Montague and Sejnowski's dopaminergic model of anticipative-predictive neural learning, is assessed as a promising, but incomplete, contribution to this approach. The paper concludes with a fourfold reflection on the divergence in cognitive modelling philosophy between the I-C and the traditional computational information processing approaches

How do concert pianists commit to memory the structure of a piece of music like Bach’s Italian Concerto, learning it well enough to remember it in the highly charged setting of a crowded performance venue, yet remaining open to the freshness of expression of the moment? Playing to this audience, in this state, now, requires openness to specificity, to interpretation, a working dynamicism that mere rote learning will not provide. Chaffin, Imreh and Crawford’s innovative and detailed research suggests that the key to this skill is a declarative mental roadmap aiding musical performance. This hypothesis is neatly and unintentionally summarized by professional pianist Imreh, who states when learning a new piece of music “My fingers were playing the notes just fine. The practice I needed was in my head. I had to learn to keep track of where I was. It was a matter of learning exactly what I needed to be thinking of as I played, and at exactly what point. . .” (Chaffin & Imreh 1997, p.326).

Tim van Gelder, following Brandom, Collins and others, uses the so‐called wide content of capacities which support social, norm governed activities, such as language, to argue for their anti‐natural, abstract, but socially instituted nature and thence for the failure of the entire traditional mind‐body discussion as ill‐posed. We argue that his former conclusion is wrong, that such properties are naturalisable, complicated organisational properties of the complexly organised, non‐linearly interactive systems that human beings are. This analysis also provides principled support, but on other grounds, for van Gelder’s latter conclusion. We outline a new naturalist approach to the organisational capacities of such systems that is intended to ground their biological, cognitive and social characters.

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

How do concert pianists commit to memory the structure of a piece of music like Bach’s Italian Concerto, learning it well enough to remember it in the highly charged setting of a crowded performance venue, yet remaining open to the freshness of expression of the moment? Playing to this audience, in this state, now, requires openness to specificity, to interpretation, a working dynamicism that mere rote learning will not provide. Chaffin, Imreh and Crawford’s innovative and detailed research suggests that the key to this skill is a declarative mental roadmap aiding musical performance. This hypothesis is neatly and unintentionally summarized by professional pianist Imreh, who states when learning a new piece of music “My fingers were playing the notes just fine. The practice I needed was in my head. I had to learn to keep track of where I was. It was a matter of learning exactly what I needed to be thinking of as I played, and at exactly what point.

Standard approaches to cognition emphasise structures (representations and rules) much more than processes, in part because this appears to be necessary to capture the normative features of cognition. However the resultant models are inflexible and face the problem of computational intractability. I argue that the ability of real world cognition to cope with complexity results from deep and subtle coupling between cognitive and non-cognitive processes. In order to capture this, theories of cognition must shift from a structural rule-defined conception of cognition to a thoroughgoing embedded process approach.

Cognitive neuroscience has come to be viewed as the flagship of the cognitive sciences and is transforming our understanding of the nature of mind. In this paper we survey several research fields in cognitive neuroscience (lateralization, neuroeconomics, and cognitive control) and note that they are making rapid progress on fundamental issues. Lateralization research is developing a comparative framework for evolutionary analysis, and is identifying individual- and population-level factors that favor brain asymmetries. Neuroeconomics is creating a research framework for studying valuation mechanisms in the brain that allows investigation of more complex phenomena than traditional reward paradigms. And cognitive control research has cast light on the mechanisms of task learning and top-down control that enable fluid goal-directed behavior in complex situations. Reasons for the success of cognitive neuroscience are varied: technical advances (e.g., in molecular genetics and imaging) are part of the story, but the more important factors have to do with the power of integrating a bottom-up mechanistic approach with larger functional and evolutionary perspectives. The incorporation of a bottom-up component differentiates cognitive neuroscience from the multidisciplinary ambitions of classical cognitive science, which suffered from having limited access to mechanisms.

Part I [sections 2–4] draws out the conceptual links between modern conceptions of teleology and their Aristotelian predecessor, briefly outlines the mode of functional analysis employed to explicate teleology, and develops the notion of cybernetic organisation in order to distinguish teleonomic and teleomatic systems. Part II is concerned with arriving at a coherent notion of intentional control. Section 5 argues that intentionality is to be understood in terms of the representational properties of cybernetic systems. Following from this, section 6 argues that intentional control needs to be seen as a particular type of relationship between the system and its environment.

The general structure of Steels & Belpaeme's (S&B's) central premise is appealing. Theoretical stances that focus on one type of mechanism miss the fact that multiple mechanisms acting in concert can provide convergent constraints for a more robust capacity than any individual mechanism might achieve acting in isolation. However, highlighting the significance of complex constraint interactions raises the possibility that some of the relevant constraints may have been left out of S&B's own models. Although abstract modeling can help clarify issues, it also runs the risk of oversimplification and misframing. A more subtle implication of the significance of interacting constraints is that it calls for a close relationship between theoretical and empirical research.

Seeking to expand on previous theories, this paper explores the AIR (Applying Intelligence to the Reflexes) approach to expert performance previously outlined by Geeves, Christensen, Sutton and McIlwain (2008). Data gathered from a semi-structured interview investigating the performance experience of Jeremy Kelshaw (JK), a professional musician, is explored. Although JK’s experience of music performance contains inherently uncertain elements, his phenomenological description of an ideal performance is tied to notions of vibe, connection and environment. The dynamic nature of music performance advocated by the AIR approach is illustrated by the strategies that JK implements during performance. Through executing these strategies, JK attempts to increase the likelihood of vibe and connection by selectively exercising agency over performance variables within his control. In order to achieve this, JK must engage in ongoing monitoring of his performance, whereby the spotlight of his attention pans across a vast array of disparate performance processes (and levels within these processes) in order to ascertain how he can most effectively meet the specific demands of a given performance situation. It is hoped that future research compiling data from numerous interviews and sources as well as using different research methodologies will further unlock the potential that the AIR approach holds for understanding expert performance.