Mind as a dynamical system (original) (raw)

A Critical Reappraisal of the Dynamical Approach to Cognition

2007

Approaches to cognitive science have been socially divided into dynamical and computational camps. We break down the dynamical approach into finer components, suggesting a new taxonomy of dynamical approaches to cognition and questioning the logical unity of the dynamical school. We dispel some confusions surrounding the concepts of dynamical systems, computation, and the relation between the two. We introduce and argue for the notion of "cognition as it could be" and show its value in analysing the dynamicists' account of time.

Dynamical Systems Theory in Cognition: Are We Really Gaining?

2011

Dynamical Systems Theory (DST) claims to be an epistemological weapon particularly broad and rich in providing a fair explanatory account of the operations of our mind. However, the very features that this DST espouses as reasons for having an edge over Computational Theory of Mind (CTM) and Artificial Neural Networks (ANN), are the ones that are causing trouble in the philosophy of science speculation, especially regarding issues of Explanation. This paper aims to suggest some possible problems that could arise from the application of DST’s characteristically abstract mathematical framework to the study of the mind. As I have not found anything that suggests something like this, my aim is to at least show the reasonability of a possibility.

Dynamical Systems in Cognition: Are We Really Gaining?

Dynamical Systems Theory (DST) claims to be an epistemological weapon particularly broad and rich in providing a fair explanatory account of the operations of our mind. However, the very features that DST espouses as reasons for having an edge over Computational Theory of Mind (CTM) and Artificial Neural Networks (ANN) are the ones that are causing trouble in the philosophy of science, especially regarding issues of Explanation. This paper aims to suggest some possible problems that could arise from the application of DST’s characteristically abstract mathematical framework to the study of the mind. As I have not found anything that suggests something like this, my aim is to at least show the reasonableness of a possibility.

Computation and dynamical models of mind

Minds and Machines, 1997

has recently spearheaded a movement to challenge the dominance of connectionist and classicist models in cognitive science. The dynamical conception of cognition is van Gelder's replacement for the computation bound paradigms provided by connectionism and classicism. He relies on the Watt governor to fulfill the role of a dynamicist Turing machine and claims that the Motivational Oscillatory Theory (MOT) provides a sound empirical basis for dynamicism. In other words, the Watt governor is to be the theoretical exemplar of the class of systems necessary for cognition and MOT is an empirical instantiation of that class. However, I shall argue that neither the Watt governor nor MOT successfully fulfill these prescribed roles. This failure, along with van Gelder's peculiar use of the concept of computation and his struggle with representationalism, prevent him from providing a convincing alternative to current cognitive theories.

Dynamical Systems Hypothesis in Cognitive Science

Encyclopedia of Cognitive Science, 2006

The dynamical hypothesis in cognition identifies various research paradigms applying the mathematics of dynamical systems to understanding cognitive function. The approach is allied with and partly inspired by research in neural science over the past fifty years for which dynamical equations have been found to provide excellent models for the behavior of single neurons (Hodgkins and Huxley, 1952). It also derives inspiration from work on gross motor activity by the limbs (e.g., Bernstein, 1967. In the early 1950s, Ashby made the startling proposal that all of cognition might be accounted for with dynamical system models (1952), but little work directly followed from his speculation due to a lack of appropriate mathematical methods and computational tools to implement practical models. More recently, the connectionist movement (Rumelhart and McClelland, 1986) provided insights and mathematical implementations of perception and learning, for example, that have helped restore interest in dynamical modeling.

Mental Representations and the Dynamic Theory of Mind

Logos & Episteme, 2012

In this paper I will investigate the possibility of defending the concept of 'mental representation' against certain contemporary critiques. Some authors, like Anthony Chemero, argue that it is possible to explain offline actions with dynamic concepts. Hence, the dynamic discourse preempts the representational one. I doubt that this is a recommendable strategy. A form of representation is necessary, though one which is different from the classical one. Instead of eliminating the concept of representation (as radical dynamicists do) or of splitting cognitive explanation in two separate discourses (as the adepts of the hybrid cognition version do), I consider that a dynamic concept of 'representation' is a better option. In my view, the higher level order resulted from the complex brain-body-environment coupling can be interpreted as being representational in nature. The dynamic paradigm involves a significant change concerning the intentional nature of representational states: the basic forms of representations are not maps of reality implemented as such in the brain, but limit conditions, attractors constraining the cognitive system's evolution in its space state to reach its goals. On a certain threshold of complexity, the system develops stable attractors and attractor landscapes which could be interpreted as standing for something outside the system. This conception offers the advantages of avoiding preemption argument, of unifying the cognitive explanation and, by its interscalar account, offers dynamic tools for building more complex artificial intelligent systems.

Cognitive Science, Representations and Dynamical Systems Theory

Studies of Nonlinear Phenomena in Life Science, 2003

In this paper we point out that the assumption of representation in the explanations and models of cognitive science has several disadvantages. We propose that the dynamical systems theory approach, emphasizing the embodied embedded nature of cognition, might provide an important, non-representational alternative. We stress the importance of the challenge, raised by Andy Clark , to dynamical systems theory to deal with 'representation-hungry' cognitive tasks. We indicate a possible way to answer that challenge in a empirically applicable manner. We suggest that investigations of this kind strengthen a motto that can be used as an antidote to the traditional representational cravings of cognitive science: 'Don't use representations in explanation and modeling unless it is absolutely necessary.'