Taxonomic Syntax for First-Order Inference

Most knowledge representation languages are based on classes and taxonomic relationships between classes. Taxonomic hierarchies without defaults or exceptions are semantically equivalent to a collection of formulas in first order predicate calculus. Although designers of knowledge representation languages often express an intuitive feeling that there must be some advantage to representing facts as taxonomic relationships rather than first order formulas, there are few, if any, technical results supporting this intuition. We attempt to remedy this situation by presenting a taxonomic syntax for first order predicate calculus and a series of theorems that support the claim that taxonomic syntax is superior to classical syntax.

Natural Language Syntax and First Order Preference

We have argued elsewhere that first order inference can be made more efficient by using non-standard syntax for first order logic. In this paper we show how a fragment of English syntax under Montague semantics provides the foundation of a new inference procedure. This procedure seems more effective than corresponding procedures based on either classical syntax of our previously proposed taxonomic syntax. This observation may provide a functional explanation for some of the syntactic structure of English.

The Proceedings of the First PHANToM User's Group Workshop

These proceedings summarize the results of the First PHANToM User's Group Workshop held September 27-30, 1996 MIT. The goal of the workshop was to bring together a group of active users of the PHANToM Haptic Interface to discuss the scientific and engineering challenges involved in bringing haptics into widespread use, and to explore the future possibilities of this exciting technology. With over 50 attendees and 25 presentations the workshop provided the first large forum for users of a common haptic interface to share results and engage in collaborative discussions. Short papers from the presenters are contained herein and address the following topics: Research Effort Overviews, Displays and Effects, Applications in Teleoperation and Training, Tools for Simulated Worlds and, Data Visualization.