David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Minds and Machines 15 (1):57-71 (2005)
Traditional approaches to modeling cognitive systems are computational, based on utilizing the standard tools and concepts of the theory of computation. More recently, a number of philosophers have argued that cognition is too subtle or complex for these tools to handle. These philosophers propose an alternative based on dynamical systems theory. Proponents of this view characterize dynamical systems as (i) utilizing continuous rather than discrete mathematics, and, as a result, (ii) being computationally more powerful than traditional computational automata. Indeed, the logical possibility of such super-powerful systems has been demonstrated in the form of analog artificial neural networks. In this paper I consider three arguments against the nomological possibility of these automata. While the first two arguments fail, the third succeeds. In particular, the presence of noise reduces the computational power of analog networks to that of traditional computational automata, and noise is a pervasive feature of information processing in biological systems. Consequently, as an empirical thesis, the proposed dynamical alternative is under-motivated: What is required is an account of how continuously valued systems could be realized in physical systems despite the ubiquity of noise
|Keywords||Cognition Computation Dynamic Metaphysics System|
|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
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Vinod Goel (1991). Notationality and the Information Processing Mind. Minds and Machines 1 (2):129-166.
Melanie Mitchell (1998). Theories of Structure Versus Theories of Change. Behavioral and Brain Sciences 21 (5):645-646.
Tony Chemero (2001). Dynamical Explanation and Mental Representations. Trends in Cognitive Sciences 5 (4):141-142.
Joe Cruz, Psychological Explanation and Noise in Modeling. Comments on Whit Schonbein's "Cognition and the Power of Continuous Dynamical Systems".
Randall D. Beer (1998). Framing the Debate Between Computational and Dynamical Approaches to Cognitive Science. Behavioral and Brain Sciences 21 (5):630-630.
Arthur B. Markman (2001). Are Dynamical Systems the Answer? Behavioral and Brain Sciences 24 (1):50-51.
Ronald L. Chrisley (1998). What Might Dynamical Intentionality Be, If Not Computation? Behavioral and Brain Sciences 21 (5):634-635.
Frank van der Velde & Marc de Kamps (1998). Toward a Synthesis of Dynamical Systems and Classical Computation. Behavioral and Brain Sciences 21 (5):652-653.
Added to index2009-01-28
Total downloads39 ( #44,663 of 1,102,801 )
Recent downloads (6 months)1 ( #296,987 of 1,102,801 )
How can I increase my downloads?