Neurally Implementable Semantic Networks
Neurons and Cognition
2013-03-19 v1 Neural and Evolutionary Computing
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.
Cite
@article{arxiv.1303.4164,
title = {Neurally Implementable Semantic Networks},
author = {Garrett N. Evans and John C. Collins},
journal= {arXiv preprint arXiv:1303.4164},
year = {2013}
}
Comments
32 pages, 12 figures