Research noteAbduction versus closure in causal theories
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Optimizing group learning: An evolutionary computing approach
2019, Artificial IntelligenceCitation Excerpt :Douven and Wenmackers' [38] aim was to compare different update rules (rules for adapting probabilities in response to new evidence) within a social setting. Specifically, they compared Bayes' rule (Oaksford & Chater [98]) with an update rule intended to formalize the kind of explanatory reasoning that has lately been much in the limelight both in artificial intelligence (Konolige [72]; Boutilier & Becher [12]; Baral [8]; Lin & You [86]; Glass [52,53]; Teijeiro & Félix [121]) and in cognitive psychology (Koslowski et al. [75]; Bes et al. [10]; Williams & Lombrozo [131]; Legare & Lombrozo [83]; Lombrozo & Gwynne [88]; Douven & Schupbach [35,36]; Lombrozo [87]; Johnston et al. [69]; Douven & Mirabile [32]; Koslowski [74]). One way in which the present paper goes beyond Douven and Wenmackers' work is by considering a number of different formalizations of explanatory reasoning, particularly ones that were motivated by the aforementioned recent work in cognitive psychology.
Nonmonotonic reasoning
2007, Handbook of the History of LogicA causal approach to nonmonotonic reasoning
2004, Artificial IntelligenceAbductive inference in defeasible reasoning: A model for research programmes
2004, Journal of Applied LogicCitation Excerpt :Moreover, we provide criteria for representing the degree of success for selecting the most successful SRP among a group in a given context. There are good characterizations of abduction of surprising observations in monotonic theories [22,28]. In normal logic programs there is a tight relationship between SLDNF and the abduction of negative literals [20].
Complexity results for explanations in the structural-model approach
2004, Artificial IntelligencePreferences and explanations
2003, Artificial Intelligence