Koichi Furukawa, Donald Michie, Stephen Muggleton (Eds.): Machine Intelligence 13, Machine Intelligence and Inductive Learning. Clarendon Press, Oxford, 1994

Historical Perspectives

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  John Alan Robinson: Logic, Computers, Turing, and von Neumann. 1-35
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  Stephen Muggleton: Logic and Learning: Turing's legacy. 37-56

Inductive Inference

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  Hiroki Arimura, Takeshi Shinohara, Setsuko Otsuki, Hiroki Ishizaka: A Generalization of the Least General Generalization. 59-85
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  Ashwin Srinivasan, Stephen Muggleton, Michael Bain: The Justification of Logical Theories based on Data Compression. 87-121
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  Ken'ichi Handa, Mikiko Nishikimi, Hitoshi Matsubara: Utilizing Structure Information in Concept Formation. 123-142
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  Hiroshi Tsukimoto, Chie Morita: The Discovery of Propositions in Noisy Data. 143-167
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  Takashi Yokomori: Learning non-deterministic finite automata from queries and counterexamples. 169-189

Scientific Domains

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  Michael J. E. Sternberg, R. A. Lewis, Ross D. King, Stephen Muggleton: Machine Learning and biomolecular modelling. 193-212
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  E. J. Kehoe: More than meets the eye: animal learning and knowledge induction. 213-246
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  C. Trevarthen: Regulation of human cognition and its growth. 247-268
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  Enn Tyugu: Large heterogeneous knowledge bases. 269-288

Experimental Machine Learning

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  Michael Bain, Stephen Muggleton: Learning optimal chess strategies. 291-309
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  Ross D. King, Bob Henery, Cao Feng, A. Sutherland: A Comparative Study of Classification Algorithms: Statistical, Machine Learning and Neural Network. 311-359

Learning Control

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  Claude Sammut: Recent progress with BOXES. 363-383
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  Donald Michie, Rui Camacho: Building symbolic representations of intuitive real-time skills from performance data. 385-418
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  Masaki Suwa, Hiroshi Motoda: Learning Perceptually Chunked Macro Operators. 419-440
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  Masayuki Numao, T. Maruoka, Masamichi Shimura: Inductively Speeding Up Logic Programs. 441-458