David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
Learn more about PhilPapers
Philosophical Psychology 18 (4):441-471 (2005)
In cognitive science, the dynamical systems theory (DST) has recently been advocated as an approach to cognitive modeling that is better suited to the dynamics of cognitive processes than the symbolic/computational approaches are. Often, the differences between DST and the symbolic/computational approach are emphasized. However, alternatively their commonalities can be analyzed and a unifying framework can be sought. In this paper, the possibility of such a unifying perspective on dynamics is analyzed. The analysis covers dynamics in cognitive disciplines, as well as in physics, mathematics and computer science. The unifying perspective warrants the development of integrated approaches covering both DST aspects and symbolic/computational aspects. The concept of a state-determined system, which is based on the assumption that properties of a given state fully determine the properties of future states, lies at the heart of DST. Taking this assumption as a premise, the explanatory problem of dynamics is analyzed in more detail. The analysis of four cases within different disciplines (cognitive science, physics, mathematics, computer science) shows how in history this perspective led to numerous often used concepts within them. In cognitive science, the concepts desire and intention were introduced, and in classical mechanics the concepts momentum, energy and force. Similarly, in mathematics a number of concepts have been developed to formalize the state-determined system assumption [e.g. derivatives (of different orders) of a function, Taylor approximations]. Furthermore, transition systems - a currently popular format for specification of dynamical systems within computer science - can also be interpreted from this perspective. One of the main contributions of the paper is that the case studies provide a unified view on the explanation of dynamics across the chosen disciplines. All approaches to dynamics analyzed in this paper share the state-determined system assumption and the (explicit or implicit) use of anticipatory state properties. Within cognitive science, realism is one of the problems identified for the symbolic/computational approach - i.e. how do internal states described by symbols relate to the real world in a natural manner. As DST is proposed as an alternative to the symbolic/computational approach, a natural question is whether, for DST, realism of the states can be better guaranteed. As a second main contribution, the paper provides an evaluation of DST compared to the symbolic/computational approach, which shows that, in this respect (i.e. for the realism problem), DST does not provide a better solution than the other approaches. This shows that DST and the symbolic/computational approach not only have the state-determined system assumption and the use of anticipatory state properties in common, but also the realism problem
|Keywords||Change Cognition Dynamics Metaphysics Model Properties State|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
Jaegwon Kim (1998). Mind in a Physical World: An Essay on the Mind-Body Problem and Mental Causation. MIT Press.
Ernest Nagel (1961). The Structure of Science: Problems in the Logic of Scientific Explanation. Harcourt, Brace & World.
Tim van Gelder & Robert Port (eds.) (1995). Mind As Motion: Explorations in the Dynamics of Cognition. MIT Press.
Gottfried Wilhelm Leibniz (1969). Philosophical Papers and Letters. D. Reidel Pub. Co..
D. W. Hamlyn & Martha Craven Nussbaum (1980). Aristotle's De Motu Animalium. Philosophical Quarterly 30 (120):246.
Citations of this work BETA
No citations found.
Similar books and articles
Damian G. Stephen & Guy van Orden (2012). Searching for General Principles in Cognitive Performance: Reply to Commentators. Topics in Cognitive Science 4 (1):94-102.
James P. Crutchfield (1998). Dynamical Embodiments of Computation in Cognitive Processes. Behavioral and Brain Sciences 21 (5):635-635.
Philip Van Loocke (2002). Deep Teleology in Artificial Systems. Minds and Machines 12 (1):87-104.
Francisco Calvo Garzón (2008). Towards a General Theory of Antirepresentationalism. British Journal for the Philosophy of Science 59 (3):259 - 292.
Thomas Pradeu (2010). The Organism in Developmental Systems Theory. Biological Theory 5 (3):216-222.
Robert W. Kentridge (1995). Symbols, Neurons, Soap-Bubbles and the Neural Computation Underlying Cognition. Minds and Machines 4 (4):439-449.
Marco Van Leeuwen (2005). Questions for the Dynamicist: The Use of Dynamical Systems Theory in the Philosophy of Cognition. [REVIEW] Minds and Machines 15 (3-4):271-333.
Tjeerd Van De Laar (2006). Dynamical Systems Theory as an Approach to Mental Causation. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 37 (2):307 - 332.
William P. Bechtel (1998). Representations and Cognitive Explanations: Assessing the Dynamicist Challenge in Cognitive Science. Cognitive Science 22 (3):295-317.
Added to index2009-01-28
Total downloads76 ( #59,112 of 1,934,581 )
Recent downloads (6 months)10 ( #52,857 of 1,934,581 )
How can I increase my downloads?