Bayesian nets and causality: philosophical and computational foundations
This book provides an introduction to, and analysis of, the use of Bayesian nets in causal modelling. It puts forward new conceptual foundations for causal network modelling: The book argues that probability and causality need to be interpreted as epistemic notions in order for the key assumptions b...
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1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Oxford
Oxford University Press
2005
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Schlagworte: | |
Online-Zugang: | UBT01 Volltext |
Zusammenfassung: | This book provides an introduction to, and analysis of, the use of Bayesian nets in causal modelling. It puts forward new conceptual foundations for causal network modelling: The book argues that probability and causality need to be interpreted as epistemic notions in order for the key assumptions behind causal models to hold. Under the epistemic view, probability and causality are understood in terms of the beliefs an agent ought to adopt. The book develops an objective Bayesian notion of probability and a corresponding epistemic theory of causality. This yields a general framework for causal modelling, which is extended to cope with recursive causal relations, logically complex beliefs and changes in an agent's language. |
Beschreibung: | Published to Oxford Scholarship Online: September 2007 |
Beschreibung: | 1 Online-Ressource (IX, 239 Seiten) |
ISBN: | 9780191712982 |
DOI: | 10.1093/acprof:oso/9780198530794.001.0001 |
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Datensatz im Suchindex
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any_adam_object | |
author | Williamson, Jon |
author_facet | Williamson, Jon |
author_role | aut |
author_sort | Williamson, Jon |
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building | Verbundindex |
bvnumber | BV045074841 |
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ctrlnum | (OCoLC)1043681820 (DE-599)BVBBV045074841 |
dewey-full | 519.5/42 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.5/42 |
dewey-search | 519.5/42 |
dewey-sort | 3519.5 242 |
dewey-tens | 510 - Mathematics |
discipline | Mathematik Philosophie Wirtschaftswissenschaften |
doi_str_mv | 10.1093/acprof:oso/9780198530794.001.0001 |
format | Electronic eBook |
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id | DE-604.BV045074841 |
illustrated | Not Illustrated |
indexdate | 2024-07-10T08:07:54Z |
institution | BVB |
isbn | 9780191712982 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030465956 |
oclc_num | 1043681820 |
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physical | 1 Online-Ressource (IX, 239 Seiten) |
psigel | ZDB-28-OSV ZDB-28-OSK ZDB-28-OSK_2007/09+2008/01 |
publishDate | 2005 |
publishDateSearch | 2005 |
publishDateSort | 2005 |
publisher | Oxford University Press |
record_format | marc |
spelling | Williamson, Jon Verfasser aut Bayesian nets and causality philosophical and computational foundations Jon Williamson Oxford Oxford University Press 2005 1 Online-Ressource (IX, 239 Seiten) txt rdacontent c rdamedia cr rdacarrier Published to Oxford Scholarship Online: September 2007 This book provides an introduction to, and analysis of, the use of Bayesian nets in causal modelling. It puts forward new conceptual foundations for causal network modelling: The book argues that probability and causality need to be interpreted as epistemic notions in order for the key assumptions behind causal models to hold. Under the epistemic view, probability and causality are understood in terms of the beliefs an agent ought to adopt. The book develops an objective Bayesian notion of probability and a corresponding epistemic theory of causality. This yields a general framework for causal modelling, which is extended to cope with recursive causal relations, logically complex beliefs and changes in an agent's language. Causalité (Physique) Kunstmatige intelligentie gtt Methode van Bayes gtt Statistique bayésienne Bayesian statistical decision theory Causality (Physics) Bayes-Netz (DE-588)4567228-3 gnd rswk-swf Bayes-Netz (DE-588)4567228-3 s b DE-604 Erscheint auch als Druck-Ausgabe 978-0-19-853079-4 https://doi.org/10.1093/acprof:oso/9780198530794.001.0001 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Williamson, Jon Bayesian nets and causality philosophical and computational foundations Causalité (Physique) Kunstmatige intelligentie gtt Methode van Bayes gtt Statistique bayésienne Bayesian statistical decision theory Causality (Physics) Bayes-Netz (DE-588)4567228-3 gnd |
subject_GND | (DE-588)4567228-3 |
title | Bayesian nets and causality philosophical and computational foundations |
title_auth | Bayesian nets and causality philosophical and computational foundations |
title_exact_search | Bayesian nets and causality philosophical and computational foundations |
title_full | Bayesian nets and causality philosophical and computational foundations Jon Williamson |
title_fullStr | Bayesian nets and causality philosophical and computational foundations Jon Williamson |
title_full_unstemmed | Bayesian nets and causality philosophical and computational foundations Jon Williamson |
title_short | Bayesian nets and causality |
title_sort | bayesian nets and causality philosophical and computational foundations |
title_sub | philosophical and computational foundations |
topic | Causalité (Physique) Kunstmatige intelligentie gtt Methode van Bayes gtt Statistique bayésienne Bayesian statistical decision theory Causality (Physics) Bayes-Netz (DE-588)4567228-3 gnd |
topic_facet | Causalité (Physique) Kunstmatige intelligentie Methode van Bayes Statistique bayésienne Bayesian statistical decision theory Causality (Physics) Bayes-Netz |
url | https://doi.org/10.1093/acprof:oso/9780198530794.001.0001 |
work_keys_str_mv | AT williamsonjon bayesiannetsandcausalityphilosophicalandcomputationalfoundations |