Abstract
Probabilistic models have started to replace classical logic as the standard reference paradigm in human deductive reasoning. Mental probability logic emphasizes general principles where human reasoning deviates from classical logic, but agrees with a probabilistic approach (like nonmonotonicity or the conditional event interpretation of conditionals). This contribution consists of two parts. In the first part we discuss general features of reasoning systems including consequence relations, how uncertainty may enter argument forms, probability intervals, and probabilistic informativeness. These concepts are of central importance for the psychological task analysis. In the second part we report new experimental data on the paradoxes of the material conditional, the probabilistic modus ponens, the complement task, and data on the probabilistic truth table task. The results of the experiments provide evidence for the hypothesis that people represent indicative conditionals by conditional probability assertions.
| Item Type: | Book Section |
|---|---|
| Faculties: | Philosophy, Philosophy of Science and Religious Science > Munich Center for Mathematical Philosophy (MCMP) Philosophy, Philosophy of Science and Religious Science > Munich Center for Mathematical Philosophy (MCMP) > Logic Philosophy, Philosophy of Science and Religious Science > Munich Center for Mathematical Philosophy (MCMP) > Philosophy of Science Philosophy, Philosophy of Science and Religious Science > Munich Center for Mathematical Philosophy (MCMP) > Philosophy of Mind |
| Subjects: | 100 Philosophy and Psychology > 100 Philosophy 100 Philosophy and Psychology > 150 Psychology |
| ISBN: | 978-1-84872-015-2 |
| Place of Publication: | Hove, UK |
| Language: | English |
| Item ID: | 19093 |
| Date Deposited: | 28. May 2014, 06:38 |
| Last Modified: | 29. Apr 2016, 09:16 |
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