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  1. A framework for explaining decision-theoretic advice.David A. Klein & Edward H. Shortliffe - 1994 - Artificial Intelligence 67 (2):201-243.
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  • Using empirical analysis to refine expert system knowledge bases.Peter Politakis & Sholom M. Weiss - 1984 - Artificial Intelligence 22 (1):23-48.
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  • The epistemology of a rule-based expert system —a framework for explanation.William J. Clancey - 1983 - Artificial Intelligence 20 (3):215-251.
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  • Automatic interpretation of loosely encoded input.James Fan, Ken Barker & Bruce Porter - 2009 - Artificial Intelligence 173 (2):197-220.
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  • The refinement of probabilistic rule sets: Sociopathic interactions.David C. Wilkins & Yong Ma - 1994 - Artificial Intelligence 70 (1-2):1-32.
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  • Human‐computer interaction: A critical synthesis.Chris Fields - 1987 - Social Epistemology 1 (1):5 – 25.
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  • Automatic knowledge base refinement for classification systems.Allen Ginsberg, Sholom M. Weiss & Peter Politakis - 1988 - Artificial Intelligence 35 (2):197-226.
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  • Learning to Troubleshoot: Multistrategy Learning of Diagnostic Knowledge for a Real‐World Problem‐Solving Task.Ashwin Ram, S. Narayanan & Michael T. Cox - 1995 - Cognitive Science 19 (3):289-340.
    This article presents a computational model of the learning of diagnostic knowledge, based on observations of human operators engaged in real-world troubleshooting tasks. We present a model of problem solving and learning in which the reasoner introspects about its own performance on the problem-solving task, identifies what it needs to learn to improve its performance, formulates learning goals to acquire the required knowledge, and pursues its learning goals using multiple learning strategies. The model is implemented in a computer system which (...)
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  • Metacognition in computation: A selected research review.Michael T. Cox - 2005 - Artificial Intelligence 169 (2):104-141.
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