MLJ 1989

22 papers

A Heuristic Approach to the Discovery of Macro-Operators Glenn A. Iba

A Study of Explanation-Based Methods for Inductive Learning Nicholas S. Flann, Thomas G. Dietterich

An Empirical Comparison of Pruning Methods for Decision Tree Induction John Mingers

An Empirical Comparison of Selection Measures for Decision-Tree Induction John Mingers

Automated Knowledge Acquisition for Strategic Knowledge Thomas R. Gruber

Automated Support for Building and Extending Expert Models Mark A. Musen

Can Machine Learning Offer Anything to Expert Systems? Bruce G. Buchanan

Conceptual Clustering, Categorization, and Polymorphy Stephen Jose Hanson, Malcolm Bauer

Efficient Specialization of Relational Concepts Kurt VanLehn

Incremental Induction of Decision Trees Paul E. Utgoff

Knowledge Acquisition for Knowledge-Based Systems: Notes on the State-of-the-Art John H. Boose, Brian R. Gaines

Learning Conjunctive Concepts in Structural Domains David Haussler

LT Revisited: Explanation-Based Learning and the Logic of Principia Mathematica Paul O'Rorke

On Learning Sets and Functions B. K. Natarajan

Semi-Supervised Learning Raymond A. Board, Leonard Pitt

Supporting Start-to-Finish Development of Knowledge Bases Ray Bareiss, Bruce W. Porter, Kenneth S. Murray

Task-Structures, Knowledge Acquisition and Learning B. Chandrasekaran

The CN2 Induction Algorithm Peter Clark, Tim Niblett

The Knowledge Level Reinterpreted: Modeling How Systems Interact William J. Clancey

The World Would Be a Better Place if Non-Programmers Could Program John P. McDermott

Toward a Unified Science of Machine Learning Pat Langley

When Will Machines Learn? Douglas B. Lenat