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Evaluating Imprecise Information in Multi-Level Decision Trees
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
2004 (English)In: 11th International Conference on the Foundations and Applications of Utility, Risk, and Decision Theory, Paris, 2004, 2004Conference paper, (Other academic)
Abstract [en]

This paper generalizes a method for handling decisions, when vague and numerically imprecise information prevails, thus extending the Delta approach into a method for handling multi-level decision trees. The straight-forward way of doing this is by using a multi-linear solver; however, this is very demanding from a computational point of view. The proposed solution is to use either backward induction or recursively collapse the multi-level decision tree into a single-level tree and thus mapping it to a bilinear problem. Restricting the format of these types of decision problems, they can be solved with reasonable computational efforts.

Place, publisher, year, edition, pages
2004.
Keyword [en]
multi-level, decision tree, imprecise, evaluation, implementation
National Category
Computer Science
Identifiers
URN: urn:nbn:se:miun:diva-1951Local ID: 1878OAI: oai:DiVA.org:miun-1951DiVA: diva2:26983
Available from: 2008-09-30 Created: 2008-09-30 Last updated: 2011-04-06Bibliographically approved
In thesis
1. Imprecise information in multi-level decision trees
Open this publication in new window or tab >>Imprecise information in multi-level decision trees
2004 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The information available to decision makers is often vague and imprecise, and various methods based

on interval estimates of probabilities and utilities have been proposed to deal with this. The discussion

has, however, mostly evolved around representation, and much less has been done to take into

consideration the evaluation, and also computational and implementation aspects has been left out.

The Delta method for handling vague and imprecise information is one of the most elaborated

approaches in its category and is therefore a reasonable starting point for this thesis. However, one

major disadvantage is that the approach only handles single-level decision trees and cannot nontrivially

be extended to handle multi-level trees. The capability of handling multi-level trees is

important, since it appears naturally in many real-life situations.

The purpose of this thesis is to present a generalization allowing for multi-level trees and imprecise

information, thus extending the Delta approach. The extension is implemented in the decision software

DecideIT, which consequently allows for interval statements and value comparisons between different

consequences, in the form of multi-level trees. Five papers are attached to the thesis. Two of these

present the necessary algorithms and an implementation employing them. The third and fourth papers

demonstrate how decision problems can be modelled and evaluated taking into account the imprecise

input data. A fifth paper presents how the method can be extended to a multi-attribute decision tree

evaluation method.

Place, publisher, year, edition, pages
Sundsvall: Mittuniversitetet, 2004. 84 p.
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 7
Keyword
multi-level, decision tree, decision analysis, decision tool, imprecise
National Category
Computer Science
Identifiers
urn:nbn:se:miun:diva-9340 (URN)91-87908-88-3 (ISBN)
Presentation
(English)
Supervisors
Available from: 2009-07-10 Created: 2009-07-10 Last updated: 2009-07-10Bibliographically approved

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Citation style
  • apa
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  • Other locale
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Output format
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