Saved in:
| Main Author: | |
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| Format: | eBook |
| Language: | English |
| Published: |
Cambridge
Cambridge University Press
2002
|
| Links: | https://doi.org/10.1017/CBO9780511546938 |
| Summary: | This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference. |
| Physical Description: | 1 Online-Ressource (xii, 294 Seiten) |
| ISBN: | 9780511546938 |
Staff View
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| indexdate | 2025-05-15T09:21:36Z |
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| isbn | 9780511546938 |
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| spelling | Xiang, Yang 1954- Probabilistic reasoning in multiagent systems a graphical models approach Yang Xiang Cambridge Cambridge University Press 2002 1 Online-Ressource (xii, 294 Seiten) txt c cr This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference. Erscheint auch als Druck-Ausgabe 9780521153904 Erscheint auch als Druck-Ausgabe 9780521813082 |
| spellingShingle | Xiang, Yang 1954- Probabilistic reasoning in multiagent systems a graphical models approach |
| title | Probabilistic reasoning in multiagent systems a graphical models approach |
| title_auth | Probabilistic reasoning in multiagent systems a graphical models approach |
| title_exact_search | Probabilistic reasoning in multiagent systems a graphical models approach |
| title_full | Probabilistic reasoning in multiagent systems a graphical models approach Yang Xiang |
| title_fullStr | Probabilistic reasoning in multiagent systems a graphical models approach Yang Xiang |
| title_full_unstemmed | Probabilistic reasoning in multiagent systems a graphical models approach Yang Xiang |
| title_short | Probabilistic reasoning in multiagent systems |
| title_sort | probabilistic reasoning in multiagent systems a graphical models approach |
| title_sub | a graphical models approach |
| work_keys_str_mv | AT xiangyang probabilisticreasoninginmultiagentsystemsagraphicalmodelsapproach |