Explanations are formulated using a theory describing the domain and the PRODIGY problem solver. Both the target concepts and the theory are declaratively ...
Recent research has demonstrated that explanation-based learning. (EBL) is a viable method for acquiring search control knowledge [22,6,18,27,29]. Almost all ...
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This paper describes how the PRODIGY system uses explanation-based specialization to learn from a variety of phenomena, including solutions, failures, ...
Sep 26, 2014 · PDF | Previous work in explanation-based learning has primarily focused on developing problem solvers that learn by observing solutions.
It introduces a definition of "operationality" based on the utility of a learned rule, and gives methods for evaluating it dynamically.
Learning Search Control Knowledge: An Explanation-Based ApproachJanuary 1988 ... Bagging strategies for learning ... to learn search control rules from experience.
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As demonstrated in this book, EBL can be used to analyze a problem solving episode in order to acquire control knowledge. Control knowledge guides the problem ...
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As demonstrated in this book, EBL can be used to analyze a problem solving episode in order to acquire control knowledge. Control knowledge guides the problem ...
This thesis analyzes the utility of EBL, and describes a method for searching for good explanations. The method, implemented in the PRODIGY/EBL system, consists ...
To produce effective control knowledge, an explanation-based learner must generate explanations that capture the key features relevant to control decisions, and ...
Missing: Strategies Approach.