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Structure information in decision trees and similar formalisms
Högskolan i Gävle.
Dept. of Computer and Systems Sciences, Forum 100, Stockholm University.
Dept. of Computer and Systems Sciences, Forum 100, Stockholm University.
2007 (English)In: Proceedings of the Twentieth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2007, 2007, 62-67 p.Conference paper, Published paper (Refereed)
Abstract [en]

In attempting to address real-life decision problems, where uncertainty about input data prevails, some kind of representation of imprecise information is important and several have been proposed over the years. In particular, first-order representations of imprecision, such as sets of probability measures, upper and lower probabilities, and interval probabilities and utilities of various kinds, have been suggested for enabling a better representation of the input sentences. A common problem is, however, that pure interval analyses in many cases cannot discriminate sufficiently between the various strategies under consideration, which, needless to say, is a substantial problem in real-life decision making in agents as well as decision support tools. This is one reason prohibiting a more wide-spread use. In this article we demonstrate that in many situations, the discrimination can be made much clearer by using information inherent in the decision structure. It is discussed using second-order probabilities which, even when they are implicit, add information when handling aggregations of imprecise representations, as is the case in decision trees and probabilistic networks. The important conclusion is that since structure carries information, the structure of the decision problem influences evaluations of all interval representations and is quantifiable.

Place, publisher, year, edition, pages
2007. 62-67 p.
Keyword [en]
Formal logic, Information analysis, Knowledge representation, Probability, Problem solving
National Category
Information Science
Identifiers
URN: urn:nbn:se:kth:diva-7339ISBN: 978-157735319-5 (print)OAI: oai:DiVA.org:kth-7339DiVA: diva2:12324
Conference
20th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2007; Key West, FL; 7 May 2007 through 9 May 2007
Note
QC 20101117Available from: 2007-06-18 Created: 2007-06-18 Last updated: 2010-11-17Bibliographically approved
In thesis
1. Distribution of expected utility in second-order decision analysis
Open this publication in new window or tab >>Distribution of expected utility in second-order decision analysis
2007 (English)Licentiate thesis, comprehensive summary (Other scientific)
Abstract [la]

In explicatione consiliorum, maxima facere communis utilitas saepe trita ratio deligendi meliorem optionem est. Verum si probabilitates et utilitates incertae vel dubiae sint, communis utilitas perturbationes affert. Studium secundi ordinis effectuum in explicatione consiliorum explanat momentum structurae quaestionium consilii, insidias aliquas ad consilium capiendum indicat et facilem ad efficiendum et intellegendum rationem comparandi varia consilia suadet. Haec thesis tractat de secundi ordinis effectibus explicationis consilii, praesertim de commune utilitate et de probabilitatibus coniunctis intervallo. Voces apertae distributionum ordinis secundi in probabilitatibus intervallo conjunctis insitarum omnino et item distributionum utilitatis expectatae in parvis quaestionibus consiliorum eduntur. His distributionibus cognitis studetur res inflexionis, aliter dictu intentio fidei.

Abstract [en]

In decision analysis maximising the expected utility is an often used approach in choosing the optimal alternative. But when probabilities and utilities are vague or imprecise expected utility is fraught with complications. Studying second-order effects on decision analysis casts light on the importance of the structure of decision problems, pointing out some pitfalls in decision making and suggesting an easy to implement and easy to understand method of comparing decision alternatives. The topic of this thesis is such second-order effects of decision analysis, particularly with regards to expected utility and interval-bound probabilities. Explicit expressions for the second-order distributions inherent in interval-bound probabilities in general and likewise for distributions of expected utility for small decision problems are produced. By investigating these distributions the phenomenon of warping, that is concentration of belief, is studied.

Place, publisher, year, edition, pages
Stockholm: KTH, 2007. vi, 20 p.
Series
Report series / DSV, ISSN 1101-8526 ; 07-006
National Category
Information Science
Identifiers
urn:nbn:se:kth:diva-4442 (URN)
Presentation
2007-06-05, Sal C, KTH-Forum, entréplanet, trapphus C, Isafjordsgatan 39, Kista, 13:00
Opponent
Supervisors
Note
QC 20101118Available from: 2007-06-18 Created: 2007-06-18 Last updated: 2010-11-18Bibliographically approved

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  • apa
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  • modern-language-association-8th-edition
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Output format
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