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020 |a9789400700086|9978-94-007-0008-6
024 7 |a10.1007/978-94-007-0008-6|2doi
041 |aeng
049 |aTürk Tarih Kurumu Kütüphanesi
050 4|aQ174-175.3
050 4|aB67
072 7|aPDA|2bicssc
072 7|aSCI075000|2bisacsh
072 7|aPDA|2thema
082 04|a501|223
090 |aDK/11748
100 1 |aHaenni, Rolf.|eauthor.|4aut|4http://id.loc.gov/vocabulary/relators/aut
245 10|aProbabilistic Logics and Probabilistic Networks|h[electronic resource] /|cby Rolf Haenni, Jan-Willem Romeijn, Gregory Wheeler, Jon Williamson.
250 |a1st ed. 2011.
264 1|aDordrecht :|bSpringer Netherlands :|bImprint: Springer,|c2011.
300 |aXIII, 155 p.|bonline resource.
336 |atext|btxt|2rdacontent
337 |acomputer|bc|2rdamedia
338 |aonline resource|bcr|2rdacarrier
347 |atext file|bPDF|2rda
490 1 |aSynthese Library, Studies in Epistemology, Logic, Methodology, and Philosophy of Science,|x2542-8292 ;|v350
505 0 |aPreface -- Part I: Probabilistic Logics -- 1. Introduction -- 2. Standard Probabilistic Semantics -- 3. Probabilistic Argumentation -- 4. Evidential Probability -- 5. Statistical Inference -- 6. Bayesian Statistical Inference -- 7. Objective Bayesian Epistemology -- Part II: Probabilistic Networks -- 8. Credal and Bayesian Networks -- 9. Networks for the Standard Semantics -- 10. Networks for Probabilistic Argumentation -- 11. Networks for Evidential Probability -- 12. Networks for Statistical Inference -- 13. Networks for Bayesian Statistical Inference -- 14. Networks for Objective Bayesianism -- 15. Conclusion -- References -- Index.
520 |aWhile probabilistic logics in principle might be applied to solve a range of problems, in practice they are rarely applied --- perhaps because they seem disparate, complicated, and computationally intractable. This programmatic book argues that several approaches to probabilistic logic fit into a simple unifying framework in which logically complex evidence is used to associate probability intervals or probabilities with sentences. Specifically, Part I shows that there is a natural way to present a question posed in probabilistic logic, and that various inferential procedures provide semantics for that question, while Part II shows that there is the potential to develop computationally feasible methods to mesh with this framework. The book is intended for researchers in philosophy, logic, computer science and statistics. A familiarity with mathematical concepts and notation is presumed, but no advanced knowledge of logic or probability theory is required.
650 0|aScience|xPhilosophy.
650 0|aComputer science|xMathematics.
650 0|aMathematical statistics.
650 0|aStatistics.
650 0|aKnowledge, Theory of.
650 0|aLogic.
650 0|aProbabilities.
650 14|aPhilosophy of Science.
650 24|aProbability and Statistics in Computer Science.
650 24|aStatistical Theory and Methods.
650 24|aEpistemology.
650 24|aLogic.
650 24|aProbability Theory.
700 1 |aRomeijn, Jan-Willem.|eauthor.|4aut|4http://id.loc.gov/vocabulary/relators/aut
700 1 |aWheeler, Gregory.|eauthor.|4aut|4http://id.loc.gov/vocabulary/relators/aut
700 1 |aWilliamson, Jon.|eauthor.|4aut|4http://id.loc.gov/vocabulary/relators/aut
710 2 |aSpringerLink (Online service)
773 0 |tSpringer Nature eBook
776 08|iPrinted edition:|z9789400700079
776 08|iPrinted edition:|z9789400700093
776 08|iPrinted edition:|z9789400734432
830 0|aSynthese Library, Studies in Epistemology, Logic, Methodology, and Philosophy of Science,|x2542-8292 ;|v350
856 40|uhttps://doi.org/10.1007/978-94-007-0008-6
912 |aZDB-2-SHU
912 |aZDB-2-SXPR
950 |aHumanities, Social Sciences and Law (SpringerNature-11648)
950 |aPhilosophy and Religion (R0) (SpringerNature-43725)