David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Minds and Machines 3 (1):53-71 (1993)
A rule-based expert system is demonstrated to have both a symbolic computational network representation and a sub-symbolic connectionist representation. These alternate views enhance the usefulness of the original system by facilitating introduction of connectionist learning methods into the symbolic domain. The connectionist representation learns and stores metaknowledge in highly connected subnetworks and domain knowledge in a sparsely connected expert network superstructure. The total connectivity of the neural network representation approximates that of real neural systems and hence avoids scaling and memory stability problems associated with other connectionist models.
|Keywords||Symbolic AI connectionist AI connectionism neural networks learning reasoning expert networks expert systems symbolic models sub-symbolic models|
|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
Paul M. Churchland & Patricia S. Churchland (1990). Could a Machine Think? Scientific American 262 (1):32-37.
John R. Searle (1990). Is the Brain's Mind a Computer Program? Scientific American 262 (1):26-31.
Citations of this work BETA
No citations found.
Similar books and articles
Roger M. Cooke (1991). Experts in Uncertainty: Opinion and Subjective Probability in Science. Oxford University Press.
Anja Oskamp (1992). Model for Knowledge and Legal Expert Systems. Artificial Intelligence and Law 1 (4):245-274.
Andy Clark (1994). Representational Trajectories in Connectionist Learning. Minds and Machines 4 (3):317-32.
Gualtiero Piccinini (2007). Connectionist Computation. In , Proceedings of the 2007 International Joint Conference on Neural Networks.
Veikko Rantala (2001). Knowledge Representation: Two Kinds of Emergence. Synthese 129 (2):195 - 209.
Reinhard Blutner (2004). Nonmonotonic Inferences and Neural Networks. Synthese 142 (2):143 - 174.
John Hawthorne (1989). On the Compatibility of Connectionist and Classical Models. Philosophical Psychology 2 (1):5-16.
Michael R. W. Dawson, D. A. Medler & Istvan S. N. Berkeley (1997). PDP Networks Can Provide Models That Are Not Mere Implementations of Classical Theories. Philosophical Psychology 10 (1):25-40.
Robin Widdison, Francis Pritchard & William Robinson (1992). The European Conflicts Guide. Artificial Intelligence and Law 1 (4):291-304.
Sorry, there are not enough data points to plot this chart.
Added to index2009-01-28
Total downloads3 ( #303,708 of 1,099,786 )
Recent downloads (6 months)3 ( #126,844 of 1,099,786 )
How can I increase my downloads?