Technical Reports

1991

@techreport{Mac1991,
	vgclass =	{report},
	vgproject =	{nn},
	author =	{Bruce MacLennan},
	title =	{Characteristics of Connectionist Knowledge
	Representation},
	number =	{CS-91-147},
	institution =	{Computer Science Department, University of Tennessee,
	Knoxville},
	month =	{November},
	year =	{1991},
	abstract =	{Connectionism -- the use of neural networks for knowledge
	representation and inference -- has profound implications for the
	representation and processing of information because it provides a
	fundamentally new view of knowledge. However, its progress is impeded
	by the lack of a unifying theoretical construct corresponding to the
	idea of a calculus (or formal system) in traditional approaches to
	knowledge representation. Such a construct, called a simulacrum, is
	proposed here, and its basic properties are explored. We find that
	although exact classification is impossible, several other useful,
	robust kinds of classification are permitted. The representation of
	structured information and constituent structure are considered, and we
	find a basis for more flexible rule-like processing than that permitted
	by conventional methods.  We discuss briefly logical issues such as
	decidability and computability and show that they require reformulation
	in this new context. Throughout we discuss the implications for
	artificial intelligence and cognitive science of this new theoretical
	framework.},
}