Machine Learning, Volume 7

Volume 7, 1991

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