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Inferential theory of learning as a conceptual basis for multistrategy learning
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Input understanding as a basis for multistrategy task-adaptive learning
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Measures of Association for Cross Classifications
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Overview of the Odysseus Learning Apprentice
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Machine Learning of Inductive Bias
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The use of explicit goals for knowledge to guide inference and learning
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Chunking in Soar: The anatomy of a general learning mechanism
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Plausible justification trees: A framework for deep and dynamic integration of learning strategies
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Learning two-tiered descriptions of flexible concepts: The POSEIDON system
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Theorem proving with abstraction
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Quantitative results concerning the utility of explanation-based learning
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Machine learning: An artificial intelligence approach (vol. 2)
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LEARNING FLEXIBLE CONCEPTS
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Acquiring Effective Search Control Rules: Explanation-Based Learning in the PRODIGY System
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Explanation-Based Generalization: A Unifying View
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DECLARATIVE BIAS FOR STRUCTURAL DOMAINS
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Abstracting Concepts with Inverse Resolution
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A Method for Multistrategy Task-adaptive Learning Based on Plausible Justifications
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Proceedings of the Sixth International Workshop on Machine Learning
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Integrated Learning: Controlling Explanation
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A HISTORY OF THE INDUCTIVE SCIENCES
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Chunking in Soar: The Anatomy of a General Learning Mechanism
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Learning Two-Tiered Descriptions of Flexible Concepts: The POSEIDON System
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Explanation-Based Generalization: A Unifying View
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Toward a Unified Theory of Learning: Multistrategy Task-adaptive Learning
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Hypothesis-Driven Constructive Induction in AQ17: A Method and Experiments
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An Experimental Comparison of Symbolic and Subsymbolic Learning Paradigms: Phase I -- Learning Logic-Style Concepts
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A Methodological Framework for Multistrategy Task-adaptive Learning
inferredcites →https://doi.org/10.13021/mars/3554openalex-snapshot
A Knowledge Representation System Based on Dynamically Interlaced Hierarchies: Basic Ideas and Examples
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How to Structure Structured Objects
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inferredcites →https://doi.org/10.7551/mitpress/3314.003.0008openalex-snapshot
Quantitative Results Concerning the Utility of Explanation-Based Learning
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Learning as Goal-Driven Inference
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