Valuation-Based Systems for Bayesian Decision Analysis
This paper proposes a new method for representing and solving Bayesian decison problems. The representation is called a valuation-based system and has some similarities to influence diagrams. However, unlike influence diagrams which emphasize conditional independence among random variables, valuatio...
| Veröffentlicht in: | Operations Research. - Institute for Operations Research and the Management Sciences, 1956. - 40(1992), 3, Seite 463-484 |
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| 1. Verfasser: | |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
1992
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| Zugriff auf das übergeordnete Werk: | Operations Research |
| Schlagworte: | Decision analysis, theory: representation, and solution using local computation Dynamic programming, Markov, finite state: solution using local computation Networks/graphs: representation for decision, optimization and probabilistic inference problems Decision Analysis, Bargaining and Negotiation Mathematics Economics Behavioral sciences Social sciences Physical sciences |
| Zusammenfassung: | This paper proposes a new method for representing and solving Bayesian decison problems. The representation is called a valuation-based system and has some similarities to influence diagrams. However, unlike influence diagrams which emphasize conditional independence among random variables, valuation-based systems emphasize factorizations of joint probability distributions. Also, whereas influence diagram representation allows only conditional probabilities, valuation-based system representation allows all probabilities. The solution method is a hybrid of local computational methods for the computation of marginals of joint probability distributions and the local computational methods for discrete optimization problems. We briefly compare our representation and solution methods to those of influence diagrams. |
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| ISSN: | 15265463 |