A program, some TECO macros, and some small modifications to existing systems software have been written, called PRO, whose purpose is to reduce the large number of control languages and system programs it has been necessary to know about and…

This reference manual consists of two parts. The first (sections 1 through 6) is intended for those who are either interested in the ITS 1.5 time sharing monitor for its own sake or who wish to write machine language programs…

The paper advocates the need for systems which support maintenance of LISP-type data bases, and describes an experimental system of this kind, call DABA. In this system, a description of the data base's structure is kept in the data base…

As advances in computer architecture and changing economics make feasible machines with large-scale parallelism, Artificial Intelligence will require new ways of thinking about computation that can exploit parallelism effectively. We present the actor model of computation as being appropriate for…

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…