Machine Learning, Volume 4

Volume 4, 1989

• Jaime G. Carbonell: Editorial. 5-6 BibTeX
• David Haussler: Learning Conjunctive Concepts in Structural Domains. 7-40 BibTeX
• Raymond A. Board, Leonard Pitt: Semi-Supervised Learning. 41-65 BibTeX
• B. K. Natarajan: On Learning Sets and Functions. 67-97 BibTeX
• Kurt VanLehn: Efficient Specialization of Relational Concepts. 99-106 BibTeX
• Thomas G. Dietterich: News and Notes. 107-109 BibTeX
• Jaime G. Carbonell: Editorial. 113-115 BibTeX
• Paul O'Rorke: LT Revisited: Explanation-Based Learning and the Logic of Principia Mathematica. 117-159 BibTeX
• Paul E. Utgoff: Incremental Induction of Decision Trees. 161-186 BibTeX
• Nicholas S. Flann, Thomas G. Dietterich: A Study of Explanation-Based Methods for Inductive Learning. 187-226 BibTeX
• John Mingers: An Empirical Comparison of Pruning Methods for Decision Tree Induction. 227-243 BibTeX
• Bruce G. Buchanan: Can Machine Learning Offer Anything to Expert Systems? 251-254 BibTeX
• Douglas B. Lenat: When Will Machines Learn? 255-257 BibTeX
• Ray Bareiss, Bruce W. Porter, Kenneth S. Murray: Supporting Start-to-Finish Development of Knowledge Bases. 259-283 BibTeX
• William J. Clancey: The Knowledge Level Reinterpreted: Modeling How Systems Interact. 285-291 BibTeX
• Thomas R. Gruber: Automated Knowledge Acquisition for Strategic Knowledge. 293-336 BibTeX
• John P. McDermott: The World Would Be a Better Place if Non-Programmers Could Program. 337-338 BibTeX
• B. Chandrasekaran: Task-Structures, Knowledge Acquisition and Learning. 339-345 BibTeX
• Mark A. Musen: Automated Support for Building and Extending Expert Models. 347-375 BibTeX
• John H. Boose, Brian R. Gaines: Knowledge Acquisition for Knowledge-Based Systems: Notes on the State-of-the-Art. 377-394 BibTeX