The studies of anatomy and physiology are fundamental ingredients of medical education. This paper identifies six ways in which such functional knowledge serves as the underpinnings for general medical reasoning, and outlines the design of a computational model of common…

We show how to interoperate, semantically and inferentially, between the leading Semantic Web approaches to rules (RuleML Logic Programs) and ontologies (OWL/DAML+OIL Description Logic) via analyzing their expressive intersection. To do so, we define a new intermediate knowledge representation (KR)…

We examine semantic interoperability problems in the fixed income securities industry
and propose a knowledge representation architecture for context interchange
mediation to support dynamic integration of autonomous database, web, and
procedural sources of information. For sources and…

Many systems have been developed for constructing decision trees from collections of examples. Although the decision trees generated by these methods are accurate and efficient, they often suffer the disadvantage of excessive complexity that can render them incomprehensible to experts.…

by Tracy S. Myers., Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1995., Includes bibliographical references (leaves 118-125).

by Richard J. Donnelly and Philip G. Potts., Thesis (S.M.M.O.T.)--Massachusetts Institute of Technology, Sloan School of Management, 1998., Vitae., Includes bibliographical references (leaves 80-81).

This is a partial theory of thinking, combining a number of classical and modern concepts from psychology, linguistics, and AI. Whenever one encounters a new situation (or makes a substantial change in one's viewpoint) he selects from memory a structure…

We had previously shown that regularization principles lead to approximation schemes, as Radial Basis Functions, which are equivalent to networks with one layer of hidden units, called Regularization Networks. In this paper we show that regularization networks encompass a much…

The thesis explores architectural form generation through two behavior based artificial intelligence approaches: the communication of agents in an unpredictable simulation system, and the codification of information within an evolutionary process. Both concepts stem from the evaluation of potentially definable…

A key problem in model-based object recognition is selection, namely, the problem of isolating regions in an image that are likely to come from a single object. This isolation can be either based solely on image data (data-driven) or can…