8. ML 1991
Lawrence Birnbaum, Gregg Collins (Eds.): Proceedings of the Eighth International Workshop (ML91), Northwestern University, Evanston, Illinois, USA. Morgan Kaufmann 1991 ISBN 1-55860-200-3
Automated Knowledge Acquisition
- Thomas R. Gruber, Catherine Baudin, John H. Boose, Jay Webber: Design Rationale Capture as Knowledge Acquisition. 3-12
- Yolanda Gil: A Domain-Independent Framework for Effective Experimentation in Planning. 13-17
- Eric K. Jones: Knowledge Refinement Using a High Level, Non-Technical Vocabulary. 18-22
- Yong Ma, David C. Wilkins: Improving the Performance of Inconsistent Knowledge Bases via Combined Optimization Method. 23-27
- Michael A. Weintraub, Tom Bylander: Generating Error Candidates for Assigning Blame in a Knowledge Base. 33-37
Computational Models of Human Learning
- Michael de la Maza: A Prototype Based Symbolic Concept Learning System. 41-45
- Mary Gick, Stan Matwin: The Importance of Causal Structure and Facts in Evaluating Explanations. 51-54
- Wayne Iba: Modeling the Acquisition and Improvement of Motor Skkills. 60-64
- Randolph M. Jones, Kurt VanLehn: A Computational Model of Acquisition for Children's Addtion Strategies. 65-69
- Rick Kazman: Babel: A Psychologically Plausible Cross-Linguistic Model of Lexical and Syntactic Acquisition. 75-79
- Sheldon Nicholl, David C. Wilkins: Computer Modelling of Acquisition Orders in Child Language. 100-104
- Thomas R. Shultz: Simulating Stages of Human Cognitive Development With Connectionist Models. 105-109
- Kurt VanLehn, Randolph M. Jones: Learning Physics Via Explanation-Based Learning of Correctness and Analogical Search Control. 110-114
Constructive Induction
- David W. Aha: Incremental Constructive Induction: An Instance-Based Approach. 117-121
- David S. Day: Learning Variable Descriptors for Applying Heuristics Across CSP Problems. 127-131
- George Drastal: Informed Pruning in Constructive Induction. 132-136
- Attilio Giordana, Lorenza Saitta, Davide Roverso: Abstracting Concepts with Inverse Resolution. 142-146
- Carl Myers Kadie: Quantifying the Value of Constructive Induction, Knowledge, and Noise Filtering on Inductive Learning. 153-157
- Adam Kowalczyk, Herman L. Ferrá, Ken Gardiner: Discovering Production Rules with Higher Order Neural Networks. 158-162
- Christopher J. Matheus: The Need for Constructive Induction. 173-177
- Arlindo L. Oliveira, Alberto L. Sangiovanni-Vincentelli: Learning Concepts by Synthesizing Minimal Threshold Gate Networks. 193-197
- Sharad Saxena: On the Effect of Instance Representation on Generalization. 198-202
- Glenn Silverstein, Michael J. Pazzani: Relational Clichés: Constraining Induction During Relational Learning. 203-207
- Richard S. Sutton, Christopher J. Matheus: Learning Polynomial Functions by Feature Construction. 208-212
- Geoffrey G. Towell, Mark Craven, Jude W. Shavlik: Constructive Induction in Knowledge-Based Neural Networks. 213-217
- Der-Shung Yang, Larry A. Rendell, Gunnar Blix: Fringe-Like Feature Construction: A Comparative Study and a Unifying Scheme. 223-227
- Dit-Yan Yeung: A Neural Network Approach to Constructive Induction. 228-232
Learning in Intelligent Information Retrieval
- David D. Lewis: Learning in Intelligent Information Retrieval. 235-239
- Jay N. Bhuyan, Vijay V. Raghavan: A Probabilistic Retrieval Scheme for Cluster-based Adaptive Information Retrieval. 240-244
- Stuart L. Crawford, Robert M. Fung, Lee A. Appelbaum, Richard M. Tong: Classification Trees for Information Retrieval. 245-249
- Sanjiv K. Bhatia, Jitender S. Deogun, Vijay V. Raghavan: Query Formulation Through Knowledge Acquisition. 250-254
- A. Goker, T. L. McCluskey: Incremental Learning in a Probalistic Information Retrieval System. 255-259
- K. L. Kwok: Query Learning Using an ANN with Adaptive Architecture. 260-264
- Paul Thompson: Machine Learning in the Combination of Expert Opinion Approach to IR. 270-274
- Steven Walczak: Predicting Actions from Induction on Past Performance. 275-279
Learning Reaction Strategies
- Matthew Brand: Decision-Theoretic Learning in an Action System. 283-287
- Steve A. Chien, Melinda T. Gervasio, Gerald DeJong: On Becoming Decreasingly Reactive: Learning to Deliberate Minimally. 288-292
- Helen G. Cobb, John J. Grefenstette: Learning the Persistence of Actions in Reactive Control Rules. 292-297
- Smadar Kedar, John L. Bresina, C. Lisa Dent: The Blind Leading the Blind: Mutual Refinement of Approximate Theories. 308-312
- Bruce Krulwich: Learning from Deliberated Reactivity. 318-322
- Long Ji Lin: Self-improvement Based on Reinforcement Learning, Planning and Teaching. 323-327
- Sridhar Mahadevan, Jonathan Connell: Scaling Reinforcement Learning to Robotics by Exploiting the Subsumption Architecture. 328-332
- Andrew W. Moore: Variable Resolution Dynamic Programming. 333-337
- David R. Pierce: Learning a Set of Primitive Actions with an Uninterpreted Sensorimotor Apparatus. 338-342
- Mark B. Ring: Incremental Development of Complex Behaviors. 343-347
- Satinder P. Singh: Transfer of Learning Across Compositions of Sequentail Tasks. 348-352
- Richard S. Sutton: Planning by Incremental Dynamic Programming. 353-357
- Ming Tan: Learning a Cost-Sensitive Internal Representation for Reinforcement Learning. 358-362
- Steven D. Whitehead: Complexity and Cooperation in Q-Learning. 363-367
- Lambert E. Wixson: Scaling Reinforcement Learning Techniques via Modularity. 3368-372
Learning Relations
- Michael Bain: Experiments in Non-Monotonic Learning. 380-384
- Ivan Bratko, Stephen Muggleton, Alen Varsek: Learning Qualitative Models of Dynamic Systems. 385-388
- Clifford Brunk, Michael J. Pazzani: An Investigation of Noise-Tolerant Relational Concept Learning Algorithms. 389-393
- Luc De Raedt, Maurice Bruynooghe, Bern Martens: Integrity Constraints and Interactive Concept-Learning. 394-398
- Saso Dzeroski, Nada Lavrac: Learning Relations from Noisy Examples: An Empirical Comparison of LINUS and FOIL. 399-402
- C. Feng: Inducing Temporal Fault Diagnostic Rules from a Qualitative Model. 403-406
- Kazuo Hiraki, John H. Gennari, Yoshinobu Yamamoto, Yuichiro Anzai: Learning Spatial Relations from Images. 407-411
- Boonserm Kijsirikul, Masayuki Numao, Masamichi Shimura: Efficient Learning of Logic Programs with Non-determinant, Non-discriminating Literals. 417-421
- Christopher Leckie, Ingrid Zukerman: Learning Search Control Rules for Planning: An Inductive Approach. 422-426
- Michael J. Pazzani, Clifford Brunk, Glenn Silverstein: A Knowledge-intensive Approach to Learning Relational Concepts. 432-436
- J. Ross Quinlan: Determinate Literals in Inductive Logic Programming. 442-446
- Céline Rouveirol: Completeness for Inductive Procedures. 452-456
- James Wogulis: Revising Relational Domain Theories. 462-466
Learning From Theory and Data
- Hamid R. Berenji: Refinement of Approximate Reasoning-based Controllers by Reinforcement Learning. 475-479
- Marco Botta, S. Ravotto, Lorenza Saitta, S. B. Sperotto: Improving Learning Using Causality and Abduction. 480-484
- Timothy Cain: The DUCTOR: A Theory Revision System for Propositional Domains. 485-489
- William W. Cohen: The Generality of Overgenerality. 490-494
- Marie desJardins: Probabilistic Evaluating of Bias for Learning Systems. 495-499
- Ronen Feldman, Alberto Maria Segre, Moshe Koppel: Incremental Refinement of Approximate Domain Theories. 500-504
- Diana F. Gordon: An Enhancer for Reactive Plans. 505-508
- Jonathan Gratch, Gerald DeJong: A Hybrid Approach to Guaranteed Effective Control Strategies. 509-513
- Rei Hamakawa: Revision Cost for Theory Refinement. 514-518
- Richard Maclin, Jude W. Shavlik: Refining Domain Theories Expressed as Finite-State Automata. 524-528
- Claire Nedellec: A Smallest Generalization Step Strategy. 529-533
- Dirk Ourston, Raymond J. Mooney: Improving Shared Rules in Multiple Category Domain Theories. 534-538
- Wei-Min Shen: Discovering Regularities from Large Knowledge Bases. 539-543
- Prasad Tadepalli: Learning with Incrutable Theories. 544-548
- Gheorghe Tecuci, Ryszard S. Michalski: A Method for Multistrategy Task-Adaptive Learning Based on Plausible Justifications. 549-553
- Bradley L. Whitehall, Stephen C. Y. Lu: A Study of How Domain Knowledge Improves Knowledge-Based Learning Systems. 559-563
- Edward J. Wisniewski, Douglas L. Medin: Is it a Pocket or a Purse? Tighly Coupled Theory and Data Driven Learing. 564-568
- Jungsoon P. Yoo, Douglas H. Fisher: Identifying Cost Effective Boundaries of Operationality. 569-573
Machine Learning in Engineering Automation
- Steve A. Chien, Bradley L. Whitehall, Thomas G. Dietterich, Richard J. Doyle, Brian Falkenhainer, James Garrett, Stephen C. Y. Lu: Machine Learning in Engineering Automation. 577-580
- Scott Bennett, Gerald DeJong: Comparing Stochastic Planning to the Acquisition of Increasingly Permissive Plans. 586-590
- Gautam Biswas, Jerry B. Weinberg, Qian Yang, Glenn R. Koller: Conceptual Clustering and Exploratory Data Analysis. 591-595
- Jason Catlett: Megainduction: A Test Flight. 596-599
- Giuseppe Cerbone, Thomas G. Dietterich: Knowledge Compilation to Speed Up Numerical Optimization. 600-604
- Ashok K. Goel: Model Revision: A Theory of Incremental Model Learning. 605-609
- Jürgen Herrmann: Learning Analytical Knowledge About VLSI-Design from Observation. 610-614
- Carl Myers Kadie: Continous Conceptual Set Covering: Learning Robot Operators From Examples. 615-619
- Paul O'Rorke, Steven Morris, Michael Amirfathi, William Bond, Daniel C. St. Clair: Machine Learning for Nondestructive Evaluation. 620-624
- Peter Pachowicz, Jerzy W. Bala: Improving Recognition Effectiveness of Noisy Texture Concepts. 625-629
- R. Bharat Rao, Stephen C. Y. Lu, Robert E. Stepp: Knowledge-Based Equation Discovery in Engineering Domains. 630-634
- Yoram Reich: Design Integrated Learning Systems for Engineering Design. 635-639
- Jeffrey C. Schlimmer: Database Consistency via Inductive Learning. 640-644
- David K. Tcheng, Bruce L. Lambert, Stephen C. Y. Lu, Larry A. Rendell: AIMS: An Adaptive Interactive Modeling System for Supporting Engineering Decision Making. 645-649
- Larry Watanabe, Sudhakar Yerramareddy: Decision Tree Induction of 3-D Manufacturing Features. 650-654
Addendum
- Mario Martin, Ramon Sangüesa, Ulises Cortés: Knowledge Acquisition Combining Analytical and Empirrcal Techniques. 657-661
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