Affiliation:
1. Department of Philosophy “Piero Martinetti”, University of Milan , Milan , Italy
Abstract
Abstract
We illustrate how a variety of logical methods and techniques provide useful, though currently underappreciated, tools in the foundations and applications of reasoning under uncertainty. The field is vast spanning logic, artificial intelligence, statistics, and decision theory. Rather than (hopelessly) attempting a comprehensive survey, we focus on a handful of telling examples. While most of our attention will be devoted to frameworks in which uncertainty is quantified probabilistically, we will also touch upon generalisations of probability measures of uncertainty, which have attracted a significant interest in the past few decades.
Reference165 articles.
1. E. T. Jaynes, Probability Theory: The Logic of Science, Cambridge University Press, Cambridge, 2003.
2. J. van Benthem, Logic and reasoning: Do the facts matter?, Studia Logica 88 (2008), no. 1, 67–84.
3. B. de Finetti, The logic of probability (1935), Philos. Stud. 77 (1935), 181–1990.
4. P. Marquis, O. Papini, and H. Prade, A Guided Tour of Artificial Intelligence Research. Vol. 1: Knowledge Representation, Reasoning and Learning, Springer, Cham, 2020.
5. J. B. Paris, A note on the Dutch book method, in: G. De Cooman, T. L. Fine, T. Seidenfeld (Eds.), ISIPTA ’01: Proceedings of the Second International Symposium on Imprecise Probabilities and Their Applications (Ithaca, NY, USA), Shaker Publishing B.V., 2001, pp. 301–306.
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1 articles.
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