The modern study of cognition finds itself with two widely endorsed but seemingly
incongruous theoretical paradigms. The first of these, inspired by formal logic and the digital …

In this thesis we consider the problems that Proper Names cause in the analysis of unedited,
naturally-occurring text. Proper Names cause problems because of their high frequency in …

Although a number of researchers have demonstrated that reasoning on a model of the
user's plans and goals is helpful in language understanding and response generation …

Abstract The Scientific Method—parsing a problem into isolated subproblems—is often
necessarily employed in optimization efforts to reduce large and complex problems into …

Connectionist networks, often known as neural networks or spreading-activation networks,
have recently been the subject of a tremendous rebirth of interest, as researchers have …

Lexical and pragmatic ambiguity is a major source of uncertainty in natural language
understanding. Symbolic models can make high-level inferences necessary for …

Building useful systems with an ability to understand" real" natural language input has long
been an elusive goal for Artificial Intelligence. Well-known problems such as ambiguity …

Cognitive agents often acquire knowledge of how devices work by reading a book. We
describe a computational theory of understanding a natural language description of a …

Is the human language understander a collection of modular processes operating with
relative autonomy, or is it a single integrated process? This ongoing debate has polarized …

The purpose of this paper is to compare different ways of adopting reason-maintenance
techniques in incremental parsing (and interpretation). A reasonmaintenance system …