David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Synthese 129 (2):195 - 209 (2001)
Two different but closely related issues in current cognitive science will be considered in this essay. One is the controversial and extensively discussed question of how connectionist and symbolic representations of knowledge are related to each other. The other concerns the notion of connectionist learning and its relevance for the understanding of the distinction between propositional and nonpropositional knowledge. More specifically, I shall give an overview of a result in Rantala and Vadén (1994) establishing a limiting case correspondence between symbolic and connectionist representations and, on the other hand, study the problem, preliminarily investigated in Rantala (1998), of how propositional knowledge may arise from nonpropositional knowledge. I shall also try to point out that on some more or less plausible assumptions, often made by cognitive scientists, these results may have some significance when we try to comprehend the nature of human knowledge representation. Some of these assumptions are rather hypothethical and debatable for the time being and they will become justified in the future only if there will be more progress in the empirical and theoretical research on the brain and on artificial networks. The assumptions concern, besides some questions of the behavior of neural networks, such things as the relevance of pattern recognition for modelling human cognition, in particular, knowledge acquisition, and the relation between emergence and reduction.
|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
Hans F. M. Crombag (1993). On the Artificiality of Artificial Intelligence. Artificial Intelligence and Law 2 (1):39-49.
Johannes Gadner, Renate Buber & Lyn Richards (eds.) (2003). Organising Knowledge: Methods and Case Studies. Palgrave Macmillan.
Martin Davies (1989). Connectionism, Modularity and Tacit Knowledge. British Journal for the Philosophy of Science 40 (December):541-55.
Edward Merrillb & Todd Petersonb (2001). From Implicit Skills to Explicit Knowledge: A Bottom‐Up Model of Skill Learning. Cognitive Science 25 (2):203-244.
Christine W. Chan (2003). Cognitive Modeling and Representation of Knowledge in Ontological Engineering. Brain and Mind 4 (2):269-282.
Deborah Osberg, Gert Biesta & Paul Cilliers (2008). From Representation to Emergence: Complexity's Challenge to the Epistemology of Schooling. Educational Philosophy and Theory 40 (1):213–227.
John Hyman (1999). How Knowledge Works. Philosophical Quarterly 50 (197):433-451.
R. C. Lacher (1993). Expert Networks: Paradigmatic Conflict, Technological Rapproachement. [REVIEW] Minds and Machines 3 (1):53-71.
Brian P. McLaughlin & F. Warfield (1994). The Allure of Connectionism Reexamined. Synthese 101 (3):365-400.
Added to index2009-01-28
Total downloads16 ( #98,837 of 1,096,702 )
Recent downloads (6 months)2 ( #162,598 of 1,096,702 )
How can I increase my downloads?