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Abductive Explanation-Based Learning: A Solution to the Multiple Inconsistent Explanation Problem

https://doi.org/10.1007/bf00992863
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Explanation-Based Learning: An Alternative View
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Learning by Failing to Explain: Using Partial Explanations to Learn in Incomplete or Intractable Domains
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The CN2 Induction Algorithm
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LEARNING FROM PLAUSIBLE EXPLANATIONS11Most of this work was completed under Prof. Don Smith at Rutgers University. Mike Pazzani, Andrea Danyluk and Bernard Silver provided valuable comments on earlier drafts of this paper.
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Explanation-Based Generalization: A Unifying View
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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On the Relation between Abduction and Inductive Learning
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Abduction in Machine Learning
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The Generate, Test, and Explain Discovery System Architecture
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Integrating induction and abduction in logic programming
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A Reply to Cohen's Book Review of Creating a Memory of Causal Relationships
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SOME METHODOLOGICAL ASPECTS OF MACHINE LEARNING
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SHAPES: A novel approach for learning search heuristics in under-constrained optimization problems
inferred← citeshttps://doi.org/10.1109/tnn.2008.2005526openalex-snapshot
Learning Without Human Expertise: A Case Study of the Double Dummy Bridge Problem
inferred← citeshttps://doi.org/10.1111/j.1467-8640.1994.tb00167.xopenalex-snapshot
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