Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Representation and Reasoning) Export

@book{citeulike:3352679, abstract = {\_Probabilistic Reasoning in Intelligent Systems\_ is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. \_Probabilistic Reasoning in Intelligent Systems\_ will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate- level courses in AI, operations research, or applied probability.}, author = {Pearl, Judea}, citeulike-article-id = {3352679}, citeulike-linkout-0 = {http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20&path=ASIN/0934613737}, citeulike-linkout-1 = {http://www.amazon.de/exec/obidos/redirect?tag=citeulike01-21&path=ASIN/0934613737}, citeulike-linkout-2 = {http://www.amazon.fr/exec/obidos/redirect?tag=citeulike06-21&path=ASIN/0934613737}, citeulike-linkout-3 = {http://www.amazon.jp/exec/obidos/ASIN/0934613737}, citeulike-linkout-4 = {http://www.amazon.co.uk/exec/obidos/ASIN/0934613737/citeulike00-21}, citeulike-linkout-5 = {http://www.amazon.com/exec/obidos/redirect?tag=citeulike07-20&path=ASIN/0934613737}, citeulike-linkout-6 = {http://www.worldcat.org/isbn/0934613737}, citeulike-linkout-7 = {http://books.google.com/books?vid=ISBN0934613737}, citeulike-linkout-8 = {http://www.amazon.com/gp/search?keywords=0934613737&index=books&linkCode=qs}, citeulike-linkout-9 = {http://www.librarything.com/isbn/0934613737}, edition = {Zweite}, howpublished = {Gebundene Ausgabe}, isbn = {0934613737}, month = {August}, posted-at = {2009-01-05 14:40:56}, priority = {2}, publisher = {Morgan Kaufmann Publishers Inc.}, title = {Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Representation and Reasoning)}, url = {http://www.amazon.com/exec/obidos/redirect?tag=citeulike07-20&path=ASIN/0934613737}, year = {1988} }

TY - BOOK ID - citeulike:3352679 L3 - citeulike-article-id:3352679 N2 - _Probabilistic Reasoning in Intelligent Systems_ is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. _Probabilistic Reasoning in Intelligent Systems_ will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate- level courses in AI, operations research, or applied probability. SN - 0934613737 TI - Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Representation and Reasoning) PB - Morgan Kaufmann Publishers Inc. AU - Pearl, Judea PY - 1988/08// UR - http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20&path=ASIN/0934613737 ER -