Facts and Possibilities: A Model-Based Theory of Sentential Reasoning
By Sangeet S. Khemlani, Ruth M. J. Byrne, Philip N. Johnson-Laird. 2018
125 citations recorded by the source corpus.
This article presents a fundamental advance in the theory of mental models as an explanation of reasoning about facts, possibilities, and probabilities. It postulates that the meanings of compound assertions, such as conditionals (if) and disjunctions (or), unlike those in logic, refer to conjunctions of epistemic possibilities that hold in default of information to the contrary. Various factors such as general knowledge can modulate these interpretations. New information can always override sentential inferences; that is, reasoning in daily life is defeasible (or nonmonotonic). The theory is a dual process one: It distinguishes between intuitive inferences (based on system 1) and deliberative inferences (based on system 2). The article describes a computer implementation of the theory, including its two systems of reasoning, and it shows how the program simulates crucial predictions that evidence corroborates. It concludes with a discussion of how the theory contrasts with those based on logic or on probabilities.
Subfields: Artificial Intelligence, General Decision Sciences, History and Philosophy of Science
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In Artificial Intelligence
In General Decision Sciences
In History and Philosophy of Science
Citations in the corpus
- Counterfactuals in Explainable Artificial Intelligence (XAI): Evidence from Human Reasoning (2019, background): “, 2007], or by the possibilities that people envisage [Khemlani et al., 2018].”