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Neurally Implementable Semantic Networks
- Publication Year :
- 2013
-
Abstract
- We propose general principles for semantic networks allowing them to be implemented as dynamical neural networks. Major features of our scheme include: (a) the interpretation that each node in a network stands for a bound integration of the meanings of all nodes and external events the node links with; (b) the systematic use of nodes that stand for categories or types, with separate nodes for instances of these types; (c) an implementation of relationships that does not use intrinsically typed links between nodes.<br />Comment: 32 pages, 12 figures
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.1303.4164
- Document Type :
- Working Paper