David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
The central claim of computationalism is generally taken to be that the brain is a computer, and that any computer implementing the appropriate program would ipso facto have a mind. In this paper I argue for the following propositions: (1) The central claim of computationalism is not about computers, a concept too imprecise for a scienti c claim of this sort, but is about physical calculi (instantiated discrete formal systems). (2) In matters of formality, interpretability, and so forth, analog computation and digital computation are not essentially di erent, and so arguments such as Searle's hold or not as well for one as for the other. (3) Whether or not a biological system (such as the brain) is computational is a scienti c matter of fact. (4) A substantive scienti c question for cognitive science is whether cognition is better modeled by discrete representations or by continuous representations. (5) Cognitive science and AI need a theoretical construct that is the continuous analog of a calculus. The discussion of these propositions will illuminate several terminology traps, in which it's all too easy to become ensnared.
|Keywords||No keywords specified (fix it)|
|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
Bruce J. MacLennan (1994). Words Lie in Our Way. Minds and Machines 4 (4):421-37.
Eric Dietrich & A. Markman (2003). Discrete Thoughts: Why Cognition Must Use Discrete Representations. Mind and Language 18 (1):95-119.
Bruce J. MacLennan (1993). Grounding Analog Computers. Think 2:8-51.
Corey J. Maley (2011). Analog and Digital, Continuous and Discrete. Philosophical Studies 155 (1):117-131.
Gualtiero Piccinini & Sonya Bahar (2013). Neural Computation and the Computational Theory of Cognition. Cognitive Science 37 (3):453-488.
Vincent C. Müller (2009). Symbol Grounding in Computational Systems: A Paradox of Intentions. [REVIEW] Minds and Machines 19 (4):529-541.
David J. Chalmers (2011). A Computational Foundation for the Study of Cognition. Journal of Cognitive Science 12 (4):323-357.
Marcin Miłkowski (2007). Is Computationalism Trivial? In Gordana Dodig Crnkovic & Susan Stuart (eds.), Computation, Information, Cognition: The Nexus and the Liminal. Cambridge Scholars Press.
James H. Fetzer (1997). Thinking and Computing: Computers as Special Kinds of Signs. [REVIEW] Minds and Machines 7 (3):345-364.
Stuart C. Shapiro (1995). Computationalism. Minds and Machines 5 (4):467-87.
Hava T. Siegelmann (2003). Neural and Super-Turing Computing. Minds and Machines 13 (1):103-114.
Daniel D. Hutto (1995). The Mindlessness of Computationalism: The Neglected Aspects of Cognition. In P. Pyllkkänen & P. Pyllkkö (eds.), New Directions in Cognitive Science. Finnish Society for Artificial Intelligence.
W. Schonbein (2005). Cognition and the Power of Continuous Dynamical Systems. Minds and Machines 15 (1):57-71.
Added to index2010-12-22
Total downloads11 ( #135,259 of 1,098,869 )
Recent downloads (6 months)1 ( #286,682 of 1,098,869 )
How can I increase my downloads?