Foundations of Knowledge Acquisition: Machine Learning
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- Artikel-Nr.: 10292233
Beschreibung
Foreword. Preface. 1. Learning = Inferencing + Memorizing; R.S. Michalski. 2. Adaptive Inference; A. Segre, C. Elkan, D. Scharstein, G. Gordon, A. Russell. 3. On Integrating Machine Learning with Planning; G.F. DeJong, M.T. Gervasio, S.W. Bennett. 4. The Role of Self-Models in Learning to Plan; G. Collins, L. Birnbaum, B. Krulwich, M. Freed. 5. Learning Flexible Concepts Using A Two-Tiered Representation; R.S. Michalski, F. Bergadano, S. Matwin., J. Zhang. 6. Competition-Based Learning; J.J. Grefenstette, K.A. De Jong, W.M. Spears. 7. Problem Solving via Analogical Retrieval and Analogical Search Control; R. Jones. 8. A View of Computational Learning Theory; L.G. Valiant. 9. The Probably Approximately Correct (PAC) and Other Learning Models; D. Haussler, M. Warmuth. 10. On the Automated Discovery of Scientific Theories; D. Osherson, S. Weinstein. Index.
Eigenschaften
Breite: | 164 |
Gewicht: | 712 g |
Höhe: | 236 |
Länge: | 26 |
Seiten: | 334 |
Sprachen: | Englisch |
Autor: | Alan L. Meyrowitz, Susan Chipman |
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