David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Kybernetika 42 (2):391--404 (2006)
An important field of probability logic is the investigation of inference rules that propagate point probabilities or, more generally, interval probabilities from premises to conclusions. Conditional probability logic (CPL) interprets the common sense expressions of the form “if . . . , then . . . ” by conditional probabilities and not by the probability of the material implication. An inference rule is probabilistically informative if the coherent probability interval of its conclusion is not necessarily equal to the unit interval [0, 1]. Not all logically valid inference rules are probabilistically informative and vice versa. The relationship between logically valid and probabilistically informative inference rules is discussed and illustrated by examples such as the modus ponens or the affirming the consequent. We propose a method to evaluate the strength of CPL inference
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Ulf Hlobil (forthcoming). Chains of Inferences and the New Paradigm in the Psychology of Reasoning. Review of Philosophy and Psychology:1-16.
Niki Pfeifer (2013). Reasoning About Uncertain Conditionals. Studia Logica (4):1-18.
Wim De Neys & Jean-François Bonnefon (2013). The 'Whys' and 'Whens' of Individual Differences in Thinking Biases. Trends in Cognitive Sciences 17 (4):172-178.
Guy Politzer (2007). Reasoning with Conditionals. Topoi 26 (1):79-95.
Niki Pfeifer & Igor Douven (2013). Formal Epistemology and the New Paradigm Psychology of Reasoning. Review of Philosophy and Psychology (2):1-23.
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