Abstract is missing.
- Generalizing from Case studies: A Case StudyDavid W. Aha. 1-10
- On Learning More ConceptsHussein Almuallim, Thomas G. Dietterich. 11-19
- The Principal Axes Method for Constructive InductionJerzy W. Bala, Ryszard S. Michalski, Janusz Wnek. 20-29
- Learning by Incomplete Explanation-Based LearningNeeraj Bhatnagar. 37-42
- Trading Off Consistency and Efficiency in version-Space InductionClaudio Carpineto. 43-48
- Peepholing: Choosing Attributes Efficiently for MegainductionJason Catlett. 49-54
- Improving Path Planning with LearningPang C. Chen. 55-61
- The Right Representation for Discovery: Finding the Conservation of MomentumPeter C.-H. Cheng, Herbert A. Simon. 62-71
- Learning to Predict in Uncertain Continuous TasksAlan D. Christiansen. 72-81
- Lazy Partial Evaluation: An Integration of Explanation-Based Generalization and Partial EvaluationPeter Clark, Robert C. Holte. 82-91
- A Teaching Method for Reinforcement LearningJeffery A. Clouse, Paul E. Utgoff. 92-110
- Spatial Analogy and SubsumptionDarrell Conklin, Janice I. Glasgow. 111-116
- Learning to Satisfy Conjunctive GoalsTimothy M. Converse, Kristian J. Hammond. 117-122
- Multistrategy Learning with Introspective Meta-ExplanationsMichael T. Cox, Ashwin Ram. 123-128
- An Asymptotic Analysis of Speedup LearningOren Etzioni. 129-136
- Why EBL Produces Overly-Specific Knowledge: A Critique of the PRODIGY ApproachesOren Etzioni, Steven Minton. 137-143
- Automatic Feature Generation for Problem Solving SystemsTom Fawcett, Paul E. Utgoff. 144-153
- Towards Inductive Generalization in Higher Order LogicCao Feng, Stephen Muggleton. 154-162
- Ordering Effects in ClusteringDouglas H. Fisher, Ling Xu, Nazih Zard. 162-168
- Learning Structured Concepts Using Genetic AlgorithmsAttilio Giordana, Claudio Sale. 169-178
- An Analysis of Learning to Plan as a Search ProblemJonathan Gratch, Gerald DeJong. 179-188
- An Approach to Anytime LearningJohn J. Grefenstette, Connie Loggia Ramsey. 189-195
- Artificial Universes - Towards a Systematic Approach to Evaluation Algorithms which Learn form ExamplesRay J. Hickey. 196-205
- Average Case Analysis of Learning kappa-CNF ConceptsDaniel S. Hirschberg, Michael J. Pazzani. 206-211
- The MENTLE Approach to Learning Heuristics for the Control of Logic ProgramsElizabeth I. Hogger, Krysia Broda. 212-217
- Fuzzy Substructure DiscoveryLawrence B. Holder, Diane J. Cook, Horst Bunke. 218-223
- Efficient Classification of Massive, Unsegmented DatastreamsLawrence Hunter, Nomi L. Harris, David J. States. 224-232
- Induction of One-Level Decision TreesWayne Iba, Pat Langley. 233-240
- Combining Competition and Cooperation in Supervised Inductive LearningCezary Z. Janikow. 241-248
- A Practical Approach to Feature SelectionKenji Kira, Larry A. Rendell. 249-256
- Learning as Optimization: Stochastic Generation of Multiple KnowledgeIgor Kononenko, Matevz Kovacic. 257-262
- Dynamic OptimizationPhilip Laird. 263-272
- Sub-unification: A Tool for Efficient Induction of Recursive ProgramsStephane Lapointe, Stan Matwin. 273-281
- Augmenting and Efficiently Utilizing Domain Theory in Explanation-Based Natural Language AcquisitionRey-Long Liu, Von-Wun Soo. 282-289
- Enhancing Transfer in Reinforcement Learning by Building Stochastic Models of Robot ActionsSridhar Mahadevan. 290-299
- THOUGHT: An Integrated Learning System for Acquiring Knowledge StructureChengjiang Mao. 300-309
- An Approach to Concept Learning Based on Term GeneralizationZdravko Markov. 310-315
- Using Transitional Proximity for Faster Reinforcement LearningAndrew McCallum. 316-321
- NFDT: A System that Learns Flexible Concepts Based on Decision Trees for Numerical AttributesThierry Van de Merckt. 322-331
- A Symbolic Algorithm for Computing Coefficients Accuracy in RegressionMarjorie Moulet. 332-337
- Compression, Significance, and AccuracyStephen Muggleton, Ashwin Srinivasan, Michael Bain. 338-347
- Guiding Example Acquisition by Generating ScenariosYves Niquil. 348-354
- Constructive Induction Using a Non-Greedy Strategy for Feature SelectionArlindo L. Oliveira, Alberto L. Sangiovanni-Vincentelli. 355-360
- Training Second-Order Recurrent Neural Networks using HintsChristian W. Omlin, C. Lee Giles. 361-366
- DYNAMIC: A New Role for Training Problems in EBLM. Alicia Pérez, Oren Etzioni. 367-372
- A Framework for Discovering Discrete Event ModelsAshvin Radiya, Jan M. Zytkow. 373-378
- Learning Episodes for OptimizationDavid Ruby, Dennis F. Kibler. 379-384
- Learning to FlyClaude Sammut, Scott Hurst, Dana Kedzier, Donald Michie. 385-393
- Deconstructing the Digit Recognition ProblemCullen Schaffer. 394-399
- On Combining Multiple Speedup TechniquesAlberto Maria Segre. 400-405
- Scaling Reinforcement Learning Algorithms by Learning Variable Temporal Resolution ModelsSatinder P. Singh. 406-415
- Detecting Novel Classes with Applications to Fault DiagnosisPadhraic Smyth, Jeff Mellstrom. 416-425
- Measuring Utility and the Design of Provably Good EBL AlgorithmsDevika Subramanian, Scott Hunter. 426-425
- Refining a Relational Theory with Multiple Faults in the Concept and SubconceptsSomkiat Tangkitvanich, Masamichi Shimura. 436-444
- Cooperation in Knowledge Base RefinementGheorghe Tecuci. 445-450
- Temporal Difference Learning of Backgammon StrategyGerald Tesauro. 451-457
- AGIL: Solving the Exploration Versus Exploration Dilemma in a single Classifier System Applied to Simulated RoboticsGilles Venturini. 458-463
- Conceptual Clustering with Systematic Missing ValuesJerry B. Weinberg, Gautam Biswas, Glenn R. Koller. 464-469
- Selecting Typical Instances in Instance-Based LearningJianping Zhang. 470-479
- The First Phase of Real-World Discovery: Determining Repeatability and Error of ExperimentsJan M. Zytkow, Jieming Zhu, Robert Zembowicz. 480-485