The Best Explanation: Criteria for Theory Choice

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Explaining Explanations: An Overview of Interpretability of Machine Learning (2018, background): “While many say it is inference [17], similar views point to the use of abductive reasoning to explain all the possible outcomes.”
INFERENCE TO THE BEST EXPLANATION (2004, unknown): “5.189; Harman, 1965; Brod y, 1970; Hanson, 1972, ch. 4; Thagard, 1978; Cartwright, 1983, essay 5).”
A Formal Definition of Intelligence Based on an Intensional Variant of Algorithmic Complexity (2003, methodology): “In this sense, we have given a formal view of Thagard’s article [Thagard 1978].”
Explanations in the wild. (2021, unknown): “This approach has focused on how well explanations subserve epistemic goals such as accurate prediction (Woodward, 2019) or how well they embody theoretic virtues such as parsimony or simplicity (Kuhn, 1977; Thagard, 1978).”
Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning (2018, background): “While many say it is inference [17], similar views point to the use of abductive reasoning to explain all the possible outcomes.”
Formalizing Multimedia Interpretation based on Abduction over Description Logic Aboxes (2009, unknown): “explanation ∆ according to the two criteria proposed by Thagard for selecting explanations [11], namely simplicity and consilience.”