David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Minds and Machines 9 (3):383-398 (1999)
Minds are said to be systematic: the capacity to entertain certain thoughts confers to other related thoughts. Although an important property of human cognition, its implication for cognitive architecture has been less than clear. In part, the uncertainty is due to lack of precise accounts on the degree to which cognition is systematic. However, a recent study on learning transfer provides one clear example. This study is used here to compare transfer in humans and feedforward networks. Simulations and analysis show, that while feedforward networks with shared weights are capable of exhibiting transfer, they cannot support the same degree of transfer as humans. One interpretation of these results is that common connectionist models lack explicit internal representations permitting rapid learning.
|Keywords||classicism connectionism Klein group learning transfer normalization systematicity weight sharing|
|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
Steven Phillips (2008). Abstract Analogies Not Primed by Relations Learned as Object Transformations. Behavioral and Brain Sciences 31 (4):393-394.
Similar books and articles
Charles Kemp, Noah D. Goodman & Joshua B. Tenenbaum (2010). Learning to Learn Causal Models. Cognitive Science 34 (7):1185-1243.
Robert F. Hadley (1993). Connectionism, Explicit Rules, and Symbolic Manipulation. Minds and Machines 3 (2):183-200.
Nicolas Szilas & Thomas R. Shultz (1997). Prospects for Automatic Recoding of Inputs in Connectionist Learning. Behavioral and Brain Sciences 20 (1):81-82.
William Bechtel (1993). Currents in Connectionism. Minds and Machines 3 (2):125-153.
Aldo Geuna & Alessandro Muscio (2009). The Governance of University Knowledge Transfer: A Critical Review of the Literature. Minerva 47 (1):93-114.
York Hagmayer, Björn Meder, Momme von Sydow & Michael R. Waldmann (2011). Category Transfer in Sequential Causal Learning: The Unbroken Mechanism Hypothesis. Cognitive Science 35 (5):842-873.
Steven Phillips (2002). Neo-Associativism: Limited Learning Transfer Without Binding Symbol Representations. Behavioral and Brain Sciences 25 (3):350-351.
Simon M. Huttegger & Brian Skyrms (2008). Emergence of Information Transfer by Inductive Learning. Studia Logica 89 (2):237 - 256.
Added to index2009-01-28
Total downloads41 ( #88,079 of 1,780,606 )
Recent downloads (6 months)5 ( #122,051 of 1,780,606 )
How can I increase my downloads?