(Enter summary)
Abstract: This paper proposes and investigates an approach to deduction in probabilistic logic, using as its medium a language that generalizes the propositional version of Nilsson's probabilistic logic by incorporating conditional probabilities. Unlike many other approaches to deduction in probabilistic logic, this approach is based on inference rules and therefore can produce proofs to explain how conclusions are drawn. We show how these rules can be incorporated into an anytime deduction procedure... (Update)
Context of citations to this paper: More
.... that have been explored in probabilistic logic, which ranges from constraints for unconditional and conditional events [AMA 91, FRI 94, LUK 99a, LUK 99b, LUK 01, NIL 86] to rich languages that specify linear inequalities over events [FAG 90] The main problems related to...
.... in model theoretic probabilistic logic, ranging from constraints for unconditional and conditional events [16, 20, 2, 53, 19, 23, 33, 45, 39, 40, 42, 46] to rich languages that specify linear inequalities over events [22] The main problems related to model theoretic...
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BibTeX entry: (Update)
A.M. Frisch and P. Haddawy. Anytime deduction for probabilistic logic. Artificial Intelligence, 69(12) :93--122, Sept 1994. http://citeseer.ist.psu.edu/frisch94anytime.html More
@article{ frisch94anytime,
author = "Alan M. Frisch and Peter Haddawy",
title = "Anytime Deduction for Probabilistic Logic",
journal = "Artificial Intelligence",
volume = "69",
number = "1--2",
pages = "93--122",
year = "1994",
url = "citeseer.ist.psu.edu/frisch94anytime.html" }
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