EWSL 88 : proceedings of the Third European Working Session on Learning, 3-5 October 1988
著者
書誌事項
EWSL 88 : proceedings of the Third European Working Session on Learning, 3-5 October 1988
Pitman, c1988
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注記
Includes bibliographies and index
内容説明・目次
内容説明
Technical papers presented at an annual conference on machine learning and artificial intelligence at the Turing Institute in Glasgow are contained in this volume, which examines the current results of various areas of research, including knowledge refinement and empirical learning methods.
目次
- Measuring quality of concept descriptions, Francesco Bergadano et al
- improving knowledge based system performance by experience, Marco Botta and L.Saitta
- learnability in the presence of noise, Stephane Boucheron and Jean Sallantin
- representing arguments as background knowledge for constraining generalization, Peter Clark
- building grammars from natural text, Alan Hutchinson
- the incremental analogy machine - a computational model of analogy, Mark Keane and Mike Brayshaw
- comparing instance-averaging with instance-filtering learning algorithms, Dennis Kibler and David W.Aha
- maching learning as an experimental science, Dennis Kibler and Pat Langley
- problem solvers that learn, Brent J.Krawchuck and Ian H.Witten
- machine learning in the next five years, D.Michie
- a strategy for constructing new predicates in first-order logic, S.Muggleton
- a study of generalization in logic programmes, Tim Niblett
- economic induction - a case study, Marlon Nunez
- integrating explanation-based and empirical learning methods in OCCAM - Michael J.Pazzani
- on interactive concept-learning and assimilation, Luc de Raedt and Maurice Bruynooghe
- learning hard concepts, Larry Rendell
- REFINER - a case-based differential diagnosis aid for knowledge acquisition and knowledge refinement, S.Sharma and D.Sleeman
- learning through progressive refinement, Walter van de Velde
- an analogical method to do incremental learning of concepts, Christel Vrain and Cheng-Ren Lu
- learning by failure to prove, Ruediger Wirth
- automatic representation adjustment in an observational discovery system, Stefan Wrobel.
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