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…

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.…

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…

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…

We have developed a method and prototype program for assisting two experts in their attempts to construct a single, consensus knowledge base. We show that consensus building can be effectively facilitated by a debugging approach that identifies, explains, and resolves…

This paper examines the issues and the solutions that have been studied in database (DB) integration research and tries to draw lessons from them for knowledge base (KB) integration.

This paper deals with the "Calculus of Knowledge", an extension of the propositional calculus in which one may reason about what other people know. Semantic and Syntactic systems are developed, certain theorems are proven, and a formal solution in the…

This paper studies the relationship of Artificial Intelligence to the study of language and the representation of the underlying knowledge which supports the comprehension process. It develops the view that intelligence is based on the ability to use large amounts…

Trying to capture intuitive knowledge is a little like trying to capture the moment between what just happened and what is about to happen. Or to quote a famous philosopher, "You can't put your foot in the same river once."…

This paper analyzes the suitability of reinforcement learning (RL) for both programming and adapting situated agents. We discuss two RL algorithms: Q-learning and the Bucket Brigade. We introduce a special case of the Bucket Brigade, and analyze and compare its…