Much Learning is done by way of studying precedents and exercises. A teacher supplies a story, gives a problem, and expects a student both to solve a problem and to discover a principle. The student must find the correspondence between…

The next generation of artificial intelligence programs will require the ability to organize knowledge as groups of active objects. Each object should have only its own local expertise, the ability to operate in parallel with other objects, and the ability…

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…

We develop a novel autonomous control synthesis strategy called Phase Space Navigator for the automatic synthesis of nonlinear control systems. The Phase Space Navigator generates global control laws by synthesizing flow shapes of dynamical systems and planning and navigating system…