Proceedings of the Fourth International Workshop on MACHINE LEARNING

Preface: The Emerging Science of Machine LearningLearning and Classification Exemplar-Based Approaches Learning About Speech Sounds: The NEXUS Project PROTOS: An Exemplar-Based Learning Apprentice Learning Representative Exemplars of Concepts: An Initial Case StudyProbabilistic Approaches Decision Trees as Probabilistic Classifiers Conceptual Clustering, Learning from Examples, and Inference How to Learn Imprecise Concepts: A Method for Employing a Two-Tiered Knowledge Representation in Learning Quasi-Darwinian Learning in a Classifier SystemConcept Learning and Bias More Robust Concept Learning Using Dynamically-Variable Bias Incremental Adjustment of Representations for LearningLearning, Problem Solving, and Planning Heuristic Search Approaches Concept Learning in Context Strategy Learning with Multilayer Connectionist Representations Learning a Preference PredicatePlanning Approaches Acquiring Effective Search Control Rules: Explanation-Based Learning in the PRODIGY System The Anatomy of a Weak Learning Method for Use in Goal Directed Search Learning and Reusing ExplanationsProblem Reduction Approaches LT Revisited: Experimental Results of Applying Explanation-Based Learning to the Logic of Principia Mathematica What is an Explanation in DISCIPLE? Extending Problem Solver Capabilities Through Case-Based InferenceLearning and Natural Language Learning to Integrate Syntax and Semantics How Do Machine-Learning Paradigms Fare in Language Acquisition? The Acquisition of PolysemyMachine Discovery Observational Discovery Cirrus: An Automated Protocol Analysis Tool Scientific Theory Formation Through Analogical Inference Inducing Causal and Social Theories: A Prerequisite for Explanation-based Learning The Role of Abstractions in Learning Qualitative ModelsDiscovery and Experimentation Learning by Experimentation Observation and Generalisation in a Simulated Robot World Empirical and Analytic Discovery in IL Combining Many Searches in the FAHRENHEIT Discovery SystemCognitive Architectures for Learning Causal Analysis and Inductive Learning Varieties of Learning in Soar: 1987 Hill-Climbing Theories of LearningOverviews Bias, Version Spaces and Valiant's Learning Framework Recent Results on Boolean Concept Learning Machine Learning from Structured Objects A New Approach to Unsupervised Learning in Deterministic Environments Searching for Operational Concept Descriptions in BAR, MetaLEX, and EBG Explanation-Based Generalization as Resolution Theorem Proving Analogy and Single-Instance GeneralizationIndex