Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

Frontcover
Morgan Kaufmann, 1988 - 552 Seiten
1 Rezension

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.

  

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Review: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

Nutzerbericht  - Zach - Goodreads

Good thorough examples and clear writing put this book ahead of most textbooks' treatment of related subjects. Despite its early publication date, it is very forward-thinking, even in terms of ... Vollständige Rezension lesen

Review: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

Nutzerbericht  - Moshe - Goodreads

I have a lot to learn about probabilistic reasoning. Vollständige Rezension lesen

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Inhalt

Chapter
1
Chapter 2
29
EXERCISES
73
EXERCISES
134
APPENDIX 3B Proof of Theorem 4
141
EXERCISES
234
FAULTS
263
EXERCISES
288
EXERCISES
374
Chapter 8
381
EXERCISES
409
Chapter 9
415
EXERCISES
465
EXERCISES
518
Author Index
539
Subject Index
545

EXERCISES
328

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Über den Autor (1988)

Judea Pearl is professor of computer science and statistics at the University of California, Los Angeles, where he directs the Cognitive Systems Laboratory and conducts research in artificial intelligence, human reasoning, and philosophy of science. The author of Heuristics and Probabilistic Reasoning, he is a member of the National Academy of Engineering and a Founding Fellow of the American Association for Artificial Intelligence. Dr Pearl is the recipient of the IJCAI Research Excellence Award for 1999, the London School of Economics Lakatos Award for 2001, and the ACM Alan Newell Award for 2004. In 2008, he received the Franklin Medal for computer and cognitive science from the Franklin Institute.

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