Machine Learning, Volume 13

Volume 13, 1993

• Ming Tan: Cost-Sensitive Learning of Classification Knowledge and Its Applications in Robotics. 7-33
• Yousri El Fattah, Paul O'Rorke: Explanation-Based Learning for Diagnosis. 35-70
• Geoffrey G. Towell, Jude W. Shavlik: Extracting Refined Rules from Knowledge-Based Neural Networks. 71-101
• Andrew W. Moore, Christopher G. Atkeson: Prioritized Sweeping: Reinforcement Learning With Less Data and Less Time. 103-130
• Ron Kohavi, Scott Benson: Research Note on Decision Lists. 131-134
• Cullen Schaffer: Selecting a Classification Method by Cross-Validation. 135-143
• Lisa Hellerstein: Book Review: ``Machine Learning: A Theoretical Approach''. 145-149
• B. K. Natarajan: A Reply to Hellerstein's Book Review of Machine Learning: A Theoretical Approach. 151-152
• Kenneth A. De Jong, William M. Spears, Diana F. Gordon: Using Genetic Algorithms for Concept Learning. 161-188
• Cezary Z. Janikow: A Knowledge-Intensive Genetic Algorithm for Supervised Learning. 189-228
• David Perry Greene, Stephen F. Smith: Competition-Based Induction of Decision Models from Examples. 229-257
• Darrell Whitley: Genetic Reinforcement Learning for Neurocontrol Problems. 259-284
• Stephanie Forrest, Melanie Mitchell: What Makes a Problem Hard for a Genetic Algorithm? Some Anomalous Results and Their Explanation. 285-319