The point of this paper is to provide a principled framework for a naturalistic, interactivist-constructivist model of rational capacity and a sketch of the model itself, indicating its merits. Being naturalistic, it takes its orientation from scientific understanding. In particular, it adopts the developing interactivist-constructivist understanding of the functional capacities of biological organisms as a useful naturalistic platform for constructing such higher order capacities as reason and cognition. Further, both the framework and model are marked by the finitude and fallibility (...) that science attributes to organisms, with their radical consequences, and also by the individual and collective capacities to improve their performances that learning organisms display. Part A prepares the ground for the exposition through a critique of the dominant Western analytic tradition in rationalising science, followed by a brief exposition of the naturalist framework that will be employed to frame the construction. This results in two sets of guidelines for constructing an alternative. Part B provides the new conception of reason as a rich complex of processes of improvement against epistemic values, and argues its merits. It closes with an account of normativity and our similarly developing rational knowledge of it, including (reflexively) of reason itself. (shrink)

Adaptation in Natural and Artificial Systems . J. H. Holland Cambridge, MA, Bradford/MIT Press, 1992.

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. (shrink)

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. (shrink)

I develop an interdisciplinary framework for understanding the nature of agents and agency that is compatible with recent developments in the metaphysics of science and that also does justice to the mechanistic and normative characteristics of agents and agency as they are understood in moral philosophy, social psychology, neuroscience, robotics, and economics. The framework I develop is internal perspectivalist. That is to say, it counts agents as real in a perspective-dependent way, but not in a way that depends on an (...) external perspective. Whether or not something counts as an agent depends on whether it is able to have a certain kind of perspective. My approach differs from many others by treating possession of a perspective as more basic than the possession of agency, representational content/vehicles, cognition, intentions, goals, concepts, or mental or psychological states; these latter capabilities require the former, not the other way around. I explain what it means for a system to be able to have a perspective at all, beginning with simple cases in biology, and show how self-contained normative perspectives about proper function and control can emerge from mechanisms with relatively simple dynamics. I then describe how increasingly complex control architectures can become organized that allow for more complex perspectives that approach agency. Next, I provide my own account of the kind of perspective that is necessary for agency itself, the goal being to provide a reference against which other accounts can be compared. Finally, I introduce a crucial distinction that is necessary for understanding human agency: that between inclinational and committal agency, and venture a hypothesis about how the normative perspective underlying committal agency might be mechanistically realized. (shrink)