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Machine Learning, Volume 7

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Volume 7, 1991

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Jaime G. Carbonell:
Editorial. Mach. Learn. 7: 5 (1991)
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Renee Elio, Larry Watanabe:
An Incremental Deductive Strategy for Controlling Constructive Induction in Learning from Examples. 7-44
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Steven D. Whitehead, Dana H. Ballard:
Learning to Perceive and Act by Trial and Error. 45-83
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Moshe Koppel:
Learning to Predict Non-Deterministically Generated Strings. 85-99
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David S. Touretzky:
Introduction. Mach. Learn. 7: 105-107 (1991)
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Sara Porat, Jerome A. Feldman:
Learning Automata from Ordered Examples. 109-138
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Michael Mozer, Jonathan Bachrach:
SLUG: A Connectionist Architecture for Inferring the Structure of Finite-State Environments. 139-160
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David Servan-Schreiber, Axel Cleeremans, James L. McClelland:
Graded State Machines: The Representation of Temporal Contingencies in Simple Recurrent Networks. 161-193
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Jeffrey L. Elman:
Distributed Representations, Simple Recurrent Networks, and Grammatical Structure. 195-225
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Jordan B. Pollack:
The Induction of Dynamical Recognizers. 227-252

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