Probabilistic reasoning in multiagent systems: a graphical models approach
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 res...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2002
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| Schlagwörter: | |
| Links: | https://doi.org/10.1017/CBO9780511546938 https://doi.org/10.1017/CBO9780511546938 https://doi.org/10.1017/CBO9780511546938 |
| Zusammenfassung: | 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 |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Umfang: | 1 online resource (xii, 294 pages) |
| ISBN: | 9780511546938 |
| DOI: | 10.1017/CBO9780511546938 |
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| 505 | 8 | 0 | |t Intelligent Agents |t Reasoning about the Environment |t Why Uncertain Reasoning? |t Multiagent Systems |t Cooperative Multiagent Probabilistic Reasoning |t Application Domains |t Bayesian Networks |t Basics on Bayesian Probability Theory |t Belief Updating Using JPD |t Graphs |t Local Computation and Message Passing |t Message Passing over Multiple Networks |t Approximation with Massive Message Passing |t Belief Updating and Cluster Graphs |t Conventions for Message Passing in Cluster Graphs |t Relation with [lambda] |g i] Message Passing |t Message Passing in Nondegenerate Cycles |t Message Passing in Degenerate Cycles |t Junction Trees |t Junction Tree Representation |t Graphical Separation |t Sufficient Message and Independence |t Encoding Independence in Graphs |t Junction Trees and Chordal Graphs |t Triangulation by Elimination |t Junction Trees as I-maps |t Junction Tree Construction |t Belief Updating with Junction Trees |t Algebraic Properties of Potentials |t Potential Assignment in Junction Trees |t Passing Belief over Separators |t Passing Belief through a Junction Tree |t Processing Observations |t Multiply Sectioned Bayesian Networks |t The Task of Distributed Uncertain Reasoning |t Organization of Agents during Communication |t Agent Interface |t Multiagent Dependence Structure |t Linked Junction Forests |t Multiagent Distributed Compilation of MSBNs |t Multiagent Moralization of MSDAG |t Effective Communication Using Linkage Trees |t Linkage Trees as I-maps |t Multiagent Triangulation |
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Datensatz im Suchindex
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|---|---|
| any_adam_object | |
| author | Xiang, Yang 1954- |
| author_facet | Xiang, Yang 1954- |
| author_role | aut |
| author_sort | Xiang, Yang 1954- |
| author_variant | y x yx |
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| bvnumber | BV043945734 |
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| collection | ZDB-20-CBO |
| contents | Intelligent Agents Reasoning about the Environment Why Uncertain Reasoning? Multiagent Systems Cooperative Multiagent Probabilistic Reasoning Application Domains Bayesian Networks Basics on Bayesian Probability Theory Belief Updating Using JPD Graphs Local Computation and Message Passing Message Passing over Multiple Networks Approximation with Massive Message Passing Belief Updating and Cluster Graphs Conventions for Message Passing in Cluster Graphs Relation with [lambda] Message Passing in Nondegenerate Cycles Message Passing in Degenerate Cycles Junction Trees Junction Tree Representation Graphical Separation Sufficient Message and Independence Encoding Independence in Graphs Junction Trees and Chordal Graphs Triangulation by Elimination Junction Trees as I-maps Junction Tree Construction Belief Updating with Junction Trees Algebraic Properties of Potentials Potential Assignment in Junction Trees Passing Belief over Separators Passing Belief through a Junction Tree Processing Observations Multiply Sectioned Bayesian Networks The Task of Distributed Uncertain Reasoning Organization of Agents during Communication Agent Interface Multiagent Dependence Structure Linked Junction Forests Multiagent Distributed Compilation of MSBNs Multiagent Moralization of MSDAG Effective Communication Using Linkage Trees Linkage Trees as I-maps Multiagent Triangulation |
| ctrlnum | (ZDB-20-CBO)CR9780511546938 (OCoLC)704478149 (DE-599)BVBBV043945734 |
| dewey-full | 006.3 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3 |
| dewey-search | 006.3 |
| dewey-sort | 16.3 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Mathematik |
| doi_str_mv | 10.1017/CBO9780511546938 |
| format | Electronic eBook |
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| id | DE-604.BV043945734 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T17:49:26Z |
| institution | BVB |
| isbn | 9780511546938 |
| language | English |
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| spelling | Xiang, Yang 1954- Verfasser aut Probabilistic reasoning in multiagent systems a graphical models approach Yang Xiang Cambridge Cambridge University Press 2002 1 online resource (xii, 294 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) Intelligent Agents Reasoning about the Environment Why Uncertain Reasoning? Multiagent Systems Cooperative Multiagent Probabilistic Reasoning Application Domains Bayesian Networks Basics on Bayesian Probability Theory Belief Updating Using JPD Graphs Local Computation and Message Passing Message Passing over Multiple Networks Approximation with Massive Message Passing Belief Updating and Cluster Graphs Conventions for Message Passing in Cluster Graphs Relation with [lambda] i] Message Passing Message Passing in Nondegenerate Cycles Message Passing in Degenerate Cycles Junction Trees Junction Tree Representation Graphical Separation Sufficient Message and Independence Encoding Independence in Graphs Junction Trees and Chordal Graphs Triangulation by Elimination Junction Trees as I-maps Junction Tree Construction Belief Updating with Junction Trees Algebraic Properties of Potentials Potential Assignment in Junction Trees Passing Belief over Separators Passing Belief through a Junction Tree Processing Observations Multiply Sectioned Bayesian Networks The Task of Distributed Uncertain Reasoning Organization of Agents during Communication Agent Interface Multiagent Dependence Structure Linked Junction Forests Multiagent Distributed Compilation of MSBNs Multiagent Moralization of MSDAG Effective Communication Using Linkage Trees Linkage Trees as I-maps Multiagent Triangulation 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 Datenverarbeitung Distributed artificial intelligence Bayesian statistical decision theory / Data processing Multiagent systems Mehragentensystem (DE-588)4389058-1 gnd rswk-swf Datenverarbeitung (DE-588)4011152-0 gnd rswk-swf Verteilte künstliche Intelligenz (DE-588)4281805-9 gnd rswk-swf Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd rswk-swf Bayes-Entscheidungstheorie (DE-588)4144220-9 s Datenverarbeitung (DE-588)4011152-0 s 1\p DE-604 Mehragentensystem (DE-588)4389058-1 s 2\p DE-604 Verteilte künstliche Intelligenz (DE-588)4281805-9 s 3\p DE-604 Erscheint auch als Druckausgabe 978-0-521-15390-4 Erscheint auch als Druckausgabe 978-0-521-81308-2 https://doi.org/10.1017/CBO9780511546938 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Xiang, Yang 1954- Probabilistic reasoning in multiagent systems a graphical models approach Intelligent Agents Reasoning about the Environment Why Uncertain Reasoning? Multiagent Systems Cooperative Multiagent Probabilistic Reasoning Application Domains Bayesian Networks Basics on Bayesian Probability Theory Belief Updating Using JPD Graphs Local Computation and Message Passing Message Passing over Multiple Networks Approximation with Massive Message Passing Belief Updating and Cluster Graphs Conventions for Message Passing in Cluster Graphs Relation with [lambda] Message Passing in Nondegenerate Cycles Message Passing in Degenerate Cycles Junction Trees Junction Tree Representation Graphical Separation Sufficient Message and Independence Encoding Independence in Graphs Junction Trees and Chordal Graphs Triangulation by Elimination Junction Trees as I-maps Junction Tree Construction Belief Updating with Junction Trees Algebraic Properties of Potentials Potential Assignment in Junction Trees Passing Belief over Separators Passing Belief through a Junction Tree Processing Observations Multiply Sectioned Bayesian Networks The Task of Distributed Uncertain Reasoning Organization of Agents during Communication Agent Interface Multiagent Dependence Structure Linked Junction Forests Multiagent Distributed Compilation of MSBNs Multiagent Moralization of MSDAG Effective Communication Using Linkage Trees Linkage Trees as I-maps Multiagent Triangulation Datenverarbeitung Distributed artificial intelligence Bayesian statistical decision theory / Data processing Multiagent systems Mehragentensystem (DE-588)4389058-1 gnd Datenverarbeitung (DE-588)4011152-0 gnd Verteilte künstliche Intelligenz (DE-588)4281805-9 gnd Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd |
| subject_GND | (DE-588)4389058-1 (DE-588)4011152-0 (DE-588)4281805-9 (DE-588)4144220-9 |
| title | Probabilistic reasoning in multiagent systems a graphical models approach |
| title_alt | Intelligent Agents Reasoning about the Environment Why Uncertain Reasoning? Multiagent Systems Cooperative Multiagent Probabilistic Reasoning Application Domains Bayesian Networks Basics on Bayesian Probability Theory Belief Updating Using JPD Graphs Local Computation and Message Passing Message Passing over Multiple Networks Approximation with Massive Message Passing Belief Updating and Cluster Graphs Conventions for Message Passing in Cluster Graphs Relation with [lambda] Message Passing in Nondegenerate Cycles Message Passing in Degenerate Cycles Junction Trees Junction Tree Representation Graphical Separation Sufficient Message and Independence Encoding Independence in Graphs Junction Trees and Chordal Graphs Triangulation by Elimination Junction Trees as I-maps Junction Tree Construction Belief Updating with Junction Trees Algebraic Properties of Potentials Potential Assignment in Junction Trees Passing Belief over Separators Passing Belief through a Junction Tree Processing Observations Multiply Sectioned Bayesian Networks The Task of Distributed Uncertain Reasoning Organization of Agents during Communication Agent Interface Multiagent Dependence Structure Linked Junction Forests Multiagent Distributed Compilation of MSBNs Multiagent Moralization of MSDAG Effective Communication Using Linkage Trees Linkage Trees as I-maps Multiagent Triangulation |
| 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 |
| topic | Datenverarbeitung Distributed artificial intelligence Bayesian statistical decision theory / Data processing Multiagent systems Mehragentensystem (DE-588)4389058-1 gnd Datenverarbeitung (DE-588)4011152-0 gnd Verteilte künstliche Intelligenz (DE-588)4281805-9 gnd Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd |
| topic_facet | Datenverarbeitung Distributed artificial intelligence Bayesian statistical decision theory / Data processing Multiagent systems Mehragentensystem Verteilte künstliche Intelligenz Bayes-Entscheidungstheorie |
| url | https://doi.org/10.1017/CBO9780511546938 |
| work_keys_str_mv | AT xiangyang probabilisticreasoninginmultiagentsystemsagraphicalmodelsapproach |