| 1986 | |  | Explanation-Based Learning: An Alternative View - Gerald Dejong and Raymond Mooney |
| | | Inductive Inference Hierarchies: Probabilistic vs Pluralistic - R. P. Daley |
| | | Probability and Measure - Patrick Billingsley |
| | | Chemical Discovery as Belief Revision - Donald Rose and Pat Langley |
| | | Editorial: Human and Machine Learning - Pat Langley |
| | | News and Notes first of 86 - Thomas G. Dietterich |
| | | Induction of Decision Trees - J. R. Quinlan |
| | | Integrating Quantitative and Qualitative Discovery: The ABACUS System - Brian C. Falkenhainer and Ryszard S. Michalski |
| | | Systems That Learn - D. Osherson, M. Stob and S. Weinstein |
| | | Parallel Distributed Processing Volume I: Foundations - D. E. Rumelhart and J. L. McClelland |
| | | Editorial: The Terminology of Machine Learning - Pat Langley |
| | | Learning Distributed Representations of Concepts - G. E. Hinton |
| | | Understanding the Nature of Learning: Issues and Research Directions - R. M. Michalski |
| | | On the Inference of Programs Approximately Computing the Desired Function - C. Smith and M. Velauthapillai |
| | | Studies on Inductive Inference from Positive Data - T. Shinohara |
| | | Determining Arguments of Invariant Functional Descriptions - Mieczyslaw M. Kokar |
| | | Learning at the Knowledge Level - Thomas G. Dietterich |
| | | Stochastic Complexity and Modeling - J. Rissanen |
| | | Chunking in Soar: The Anatomy of a General Learning Mechanism - John E. Laird, Paul S. Rosenbloom and Allen Newell |
| | | An Algebraic Framework for Inductive Program Synthesis - K. P. Jantke |
| | | The disjunctive Learning Problem - M. Fulk |
| | | Machine Learning of Nearly Minimal Size Grammars - J. Case and H. Chi |
| | | On Barzdin’s Conjecture - T. Zeugmann |
| | | A General Framework for Parallel Distributed Processing - D. E. Rumelhart, G. E. Hinton and J. L. McClelland |
| | | Machine Learning: An Artificial Intelligence Approach 2 - R. S. Michalski and J. G. Carbonell and T. M. Mitchell |
| | | On the Complexity of Inductive Inference - R. Daley and C. Smith |
| | | Using telltales in developing program test sets - J. Cherniavsky and C. Smith |
| | | A General Framework for Induction and a Study of Selective Induction - Larry Rendell |
| | | On The Inference of Sequences of Functions - W. Gasarch and C. Smith |
| | | Inductive inference by refinement - P. Laird |
| | | Distributional Expectations and the Induction of Category Structure - M. J. Flannagan, L. S. Fried and K. J. Holyoak |
| | | Inductive Inference of Functions From Noised Observations - J. Grabowski |
| | | Learning Concepts by Asking Questions - C. Sammut and R. Banerji |
| | | News and Notes - Thomas G. Dietterich, Nicholas S. Flann and David C. Wilkins |
| | | Experimental Goal Regression: A Method for Learning Problem-Solving Heuristics - Bruce W. Porter and Dennis F. Kibler |
| | | Machine Learning and Discovery - Pat Langley and Ryszard S. Michalski |
| | | Incremental Learning from Noisy Data - Jeffrey C. Schlimmer and Jr. Richard H. Granger |
| | | Linear Function Neurons: Structure and Training - S. E. Hampson and D. J. Volper |
| | | A Theory of Historical Discovery: The Construction of Componential Models - Jan M. Zytkow and Herbert A. Simon |
| | | Explanation-Based Generalization: A Unifying View - Tom M. Mitchell, Richard M. Keller and Smadar T. Kedar-Cabelli |
| | | Aggregating Inductive Expertise - D. Osherson, M. Stob and S. Weinstein |
| | | A Framework for Empirical Discovery - P. Langley and B. Nordhausen |
| | | Inductive Inference of approximations - J. Royer |
| | | A General Theory of Discrimination Learning - P. Langley |
| | | On the Inductive Inference of Programs with Anomalies - M. Velauthapillai |
| | | News and Notes - Yves Kodratoff, Gheorghes Tecuci and Thomas G. Dietterich |
| | | On Machine Learning - Pat Langley |
| | | Learning Representations By Back-Propagating Errors - D. E. Rumelhart, G. E. Hinton and R. J. Williams |
| | | Some Problems on Inductive Inference from Positive Data - T. Shinohara |
| | | Learning Internal Representations by Error Propagation - D. E. Rumelhart, G. E. Hinton and R. J. Williams |
| | | A Theory and Methodology of Inductive Inference - R. S. Michalski |
| | | Learning Machines - J. Case |
| | | Identification in the Limit of First Order Structures - D. N. Osherson and S. Weinstein |
| | | Parallel Distributed Processing - Explorations in the Microstructure of Cognition - J. L. McClelland, D. E. Rumelhart and t. P. R. Group |
| | | Stochastic Complexity and Sufficient Statistics - J. Rissanen |
| | | How Fast is Program Synthesis from Examples - R. Wiehagen |
| | | Some Results in the Theory of Effective Program Synthesis - Learning by Defective Information - G. Schäfer-Richter |
| | | An Analysis of a Learning Paradigm - D. Osherson, M. Stob and S. Weinstein |
| | | On the Complexity of Effective Program Synthesis - R. Wiehagen |
| | | Systems that Learn: An Introduction to Learning Theory for Cognitive and Computer Scientists - D. N. Osherson, M. Stob and S. Weinstein |
| | | Stratified Inductive Hypothesis Generation - Z. S. Szabo |
| | | Stochastic Relaxation Methods for Image Restoration and Expert Systems - S. Geman |
| | | Machine Learning of Inductive Bias - P. E. Utgoff |
| | | On the Complexity of Program Synthesis from Examples - R. Wiehagen |
| | | Learning from positive-only examples - R. Berwick |
| | | Towards the Development of an Analysis of Learning Algorithms - R. Daley |
| | | The Effect of Noise on Concept Learning - J. R. Quinlan |
| January | | An Introduction to Hidden Markov Models - L. R. Rabiner and B. H. Juang |
| February | | Genetic AI-Translating Piaget into Lisp - G. L. Drescher |
| May | | On the Logic of Representing Dependencies by Graphs - J. Pearl and A. Paz |
| | | CONSENSUS: A Statistical Learning Procedure in a Connectionist Network - G. J. Goetsch |
| June | | Types of queries for concept learning - D. Angluin |
| | | A Lemma on the Multiarmed Bandit Problem - J. N. Tsitsiklis |
| October | | Analogical and Inductive Inference, International Workshop AII ’86. Wendisch-Rietz, GDR - K. P. Jantke |
