Explanatory coherence

By Paul Thagard. 1993

How researchers see this paper

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

Citations in the corpus

Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, background): “achamer, Darden, and Craver, 2000; Marr and Poggio, 1976; Maxwell, 1974; Maze, 1954; Meissner, 1960; Rozeboom, 1956; Rozenblit and Keil, 2002; Scriven, 1958; Simon, 1992; Smith, 2014; Strevens, 2004; Thagard, 1989; Thorpe, 1974; Van Der Linden, Leiserowitz, Rosenthal, and Maibach, 2017; Wilkenfeld, ”
Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences (2017, background): “Recent work shows that people prefer explanations that are simpler (cite few causes) [Lombrozo, 2007], more general (they explain more events) [Lombrozo, 2007], and coherent (consistent with prior knowledge) [Thagard, 1989].”
Explanation in Artificial Intelligence: Insights from the Social Sciences (2017, background): “Read and Marcus-Newhall [152] tested the hypotheses from Thagard’s theory of explanatory coherence [170] that people prefer simpler and more general explanations.”
The Explanatory Power of Valuable Beliefs (2005, background): “The idea that beliefs serve as explanations is certainly not new (e.g., Allport, 1935; Frazer, 1890/1923; Thagard, 1989).”
Beyond dual-process models: A categorisation of processes underlying intuitive judgement and decision making (2010, methodology): “…processes can be captured mathematically using parallel constraint satisfaction (PCS) network models, which have also been repeatedly applied to judgements and decisions (Glöckner & Betsch, 2008c; Glöckner & Herbold, in press; Holyoak & Simon, 1999; Thagard, 1989; Thagard & Millgram, 1995).”
Knowledge Revision Processes in Refutation Texts (2014, unknown): “…(e.g., Carey, 2000, 2009; Chi, 2008; Chi, Slotta, & deLeeuw, 1994; Chinn & Brewer, 1993, 1998; Clark, 2006; diSessa, 1998, 2008; Dole & Sinatra, 1998; Hynd & Guzzetti, 1998; Linn, 2008; Nersessian, 2008; Ohlsson, 2009; Posner et al., 1982; Sinatra & Pintrich, 2003; Thagard, 2008; Vosniadou, 2008).”
Explanation and Abductive Inference (2012, background): “…include simplicity (Bonawitz & Lombrozo, in press; Lagnado, 1994; Lombrozo, 2007; Read & Marcus-Newhall, 1993; Thagard, 1989), breadth (Preston & Epley, 2005; Read & Marcus-Newhall, 1993; Thagard, 1989), consistency with prior knowledge (Thagard, 1989), and coherence (Pennington & Hastie, 1993).”
Structural Dynamics of Cognition: From Consistency Theories to Constraint Satisfaction (2002, methodology): “…processes, including analogical mapping (the ACME model of Holyoak & Thagard, 1989; Spellman & Holyoak, 1992), evaluation of competing explanations (the ECHO model of Thagard, 1989, 1992; see also Read & Marcus-Newhall, 1993), and decision making (the DECO model of Thagard & Millgram, 1995).”
Simplicity and probability in causal explanation. (2007, unknown): “Non-probabilistic approaches like Thagard (1989, 2000) and Read and Marcus-Newhall (1993) predict that participants will always select the simpler explanation, regardless of the disease baserates.”
Explaining by Removing: A Unified Framework for Model Explanation (2020, background): “Richer information may not always be desirable, because psychology research shows that people report higher satisfaction with explanations that cite fewer causes (Thagard, 1989; Read and Marcus-Newhall, 1993; Lombrozo, 2007; Miller, 2019).”
Special Thematic Section on "Societal Change" A Complex Systems Approach to the Study of Ideology: Cognitive-Affective Structures and the Dynamics of Belief Systems (2013, background): “Like their non-adaptive cousins, adaptive complex systems exhibit density and recursivity of connections along with and/or causal aggregators.”