Date of Original Version



Technical Report

Rights Management

All Rights Reserved

Abstract or Description

Abstract: "It is well accepted that knowledge base development and maintenance costs are key obstacles to the further proliferation of knowledge-based systems. We consider here an approach to dramatically reduce this cost by developing learning apprentice systems: knowledge-based advisors which learn from their users throughout their life-cycle. In particular, we present a learning apprentice for calendar management, which allows users to schedule meetings and provides advice regarding parameters such as the meeting time, duration, topic, and location. Each observed user's decision is used as a training example of the correct decision in the current context.The system learns to provide increasingly competent advice by generalizing from these training examples. We present preliminary results showing that knowledge automatically acquired by two learning methods (ID3 and Back-Propagation) compares favorably to manually developed rules when used to schedule meetings for a university faculty member. The system has recently been put into use on a regular basis by one secretary in our environement [sic] and is currently undergoing further testing and development."