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001 978-94-007-0008-6
003 DE-He213
005 20140220083827.0
007 cr nn 008mamaa
008 101119s2011 ne | s |||| 0|eng d
020 _a9789400700086
_9978-94-007-0008-6
024 7 _a10.1007/978-94-007-0008-6
_2doi
050 4 _aB67
072 7 _aPDA
_2bicssc
072 7 _aSCI075000
_2bisacsh
082 0 4 _a501
_223
100 1 _aHaenni, Rolf.
_eauthor.
245 1 0 _aProbabilistic Logics and Probabilistic Networks
_h[electronic resource] /
_cby Rolf Haenni, Jan-Willem Romeijn, Gregory Wheeler, Jon Williamson.
264 1 _aDordrecht :
_bSpringer Netherlands,
_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 ;
_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 _aPhilosophy (General).
650 0 _aGenetic epistemology.
650 0 _aLogic.
650 0 _aScience
_xPhilosophy.
650 0 _aComputer science.
650 0 _aDistribution (Probability theory).
650 0 _aMathematical statistics.
650 1 4 _aPhilosophy.
650 2 4 _aPhilosophy of Science.
650 2 4 _aProbability and Statistics in Computer Science.
650 2 4 _aStatistical Theory and Methods.
650 2 4 _aEpistemology.
650 2 4 _aLogic.
650 2 4 _aProbability Theory and Stochastic Processes.
700 1 _aRomeijn, Jan-Willem.
_eauthor.
700 1 _aWheeler, Gregory.
_eauthor.
700 1 _aWilliamson, Jon.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9789400700079
830 0 _aSynthese Library, Studies in Epistemology, Logic, Methodology, and Philosophy of Science ;
_v350
856 4 0 _uhttp://dx.doi.org/10.1007/978-94-007-0008-6
912 _aZDB-2-SHU
999 _c109173
_d109173