miun.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Imprecise information in multi-level decision trees
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
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. , p. 84
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 7
Keywords [en]
multi-level, decision tree, decision analysis, decision tool, imprecise
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:miun:diva-9340ISBN: 91-87908-88-3 (print)OAI: oai:DiVA.org:miun-9340DiVA, id: diva2:227274
Presentation
(English)
Supervisors
Available from: 2009-07-10 Created: 2009-07-10 Last updated: 2018-01-13Bibliographically approved
List of papers
1. Evaluating Imprecise Information in Multi-Level Decision Trees
Open this publication in new window or tab >>Evaluating Imprecise Information in Multi-Level Decision Trees
2004 (English)In: 11th International Conference on the Foundations and Applications of Utility, Risk, and Decision Theory, Paris, 2004, 2004Conference paper, Published 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.

Keywords
multi-level, decision tree, imprecise, evaluation, implementation
National Category
Computer Sciences
Identifiers
urn:nbn:se:miun:diva-1951 (URN)1878 (Local ID)1878 (Archive number)1878 (OAI)
Available from: 2008-09-30 Created: 2008-09-30 Last updated: 2018-01-12Bibliographically approved
2. The DecideIT Decision Tool
Open this publication in new window or tab >>The DecideIT Decision Tool
2003 (English)In: ISIPTA '03: Proceedings of the Third International Symposium on Imprecise Probabilities and Their Applications, Lugano, Switzerland, July 14-17, 2003, Carleton Scientific , 2003, p. 204-217Conference paper, Published paper (Other academic)
Abstract [en]

The nature of much information available to decision makers is vague and imprecise, be it information for human managers in organisations or for process agents in a distributed computer environment. Several models for handling vague and imprecise information in decision situations have been suggested. In particular, various interval methods have prevailed, i.e. methods based on interval estimates of probabilities and, in some cases, interval utility estimates. Even if these approaches in general are well founded, little has been done to take into consideration the evaluation perspective and, in particular, computational aspects and implementation issues. The purpose of this paper is to demonstrate a tool for handling imprecise information in decision situations. The tool is an implementation of our earlier research focussing on finding fast algorithms for solving bilinear systems of equations together with a graphical user interface supporting the interpretation of evaluations of imprecise data.

Place, publisher, year, edition, pages
Carleton Scientific, 2003
Keywords
Decision Analysis, Interval Probabilities, Utility Theory, Decision Tools.
National Category
Computer Sciences
Identifiers
urn:nbn:se:miun:diva-1690 (URN)315 (Local ID)1-894145-17-8 (ISBN)315 (Archive number)315 (OAI)
Projects
PI - Publika Informationssystem
Available from: 2008-11-23 Created: 2008-11-23 Last updated: 2018-01-12Bibliographically approved
3. Investment Decision Analysis: a case study at SCA Transforest
Open this publication in new window or tab >>Investment Decision Analysis: a case study at SCA Transforest
2003 (English)In: IKE'03: Proceedings of the international conference on infomration and knowledge engineering: Vols. 1 and 2, 2003, p. 79-85Conference paper, Published paper (Other scientific)
Abstract [en]

In investment decision-making in organizations, large values can be at stake. The need for a structured process is evident, not least when several people or interests are involved in the process. We advocate that the use of modern computational decision analysis can improve such investment processes by improving visibility and only requiring reasonably precise input data. The applicability of a structured decision analysis to corporate decision-making is demonstrated in a case study at SCA Transforest, a subdivision to SCA. The decision problem consists of whether a new system for logistic control should be implemented or not. The background information was collected through interviews and the structuring and analysis of the problem was performed using the tool DecideIT, designed for handling situations where uncertainties in input data prevail. The result of the analysis points out a reasonable action, but also shows which aspects are crucial to consider for a reliable result.

Keywords
Decision analysis, Decision tools, Vague information, Decision support system
National Category
Computer Sciences
Identifiers
urn:nbn:se:miun:diva-1299 (URN)314 (Local ID)1-932415-09-2 (ISBN)314 (Archive number)314 (OAI)
Available from: 2008-11-23 Created: 2008-11-23 Last updated: 2018-01-12Bibliographically approved
4. Decision Evaluation of Three Flood Management Strategies.
Open this publication in new window or tab >>Decision Evaluation of Three Flood Management Strategies.
2003 (English)In: FLAIRS' 03 Recent Advances in Artificial Intelligence: Proceedings of the 16th International Flairs Conference, Menlo Park, Calif.: AAAI Press , 2003, p. 491-495Conference paper, Published paper (Other scientific)
Abstract [en]

This article describes the application of computational decision analytic techniques for a national policy decision. It constitutes an example of the increasing use of modern computational decision methods to assist in decision-making in society. An integrated flood catastrophe model is presented as well as some results of a case study made in the Upper Tisza region in north-eastern Hungary, viz. the Palad-Csecsei basin. Background data was provided through the Hungarian Academy of Sciences and complemented by interviews with different stakeholders in the region. Based upon these data, where a large degree of uncertainty is prevailing, we demonstrate how an implementation of a simulation and decision analytical model can provide insights into the effects of imposing different policy options for a flood risk management program in the region. We focus herein primarily on general options for designing a public/private insurance and reinsurance system for Hungary. It should, however, be emphasized that the main purpose of this article is not to provide any definite recommendations, but rather to present a methodology for handling a set of policy packages with the aim of gaining a consensus among stakeholders.

Place, publisher, year, edition, pages
Menlo Park, Calif.: AAAI Press, 2003
Keywords
decision analysis
National Category
Computer Sciences
Identifiers
urn:nbn:se:miun:diva-1674 (URN)313 (Local ID)1-57735-177-0 (ISBN)313 (Archive number)313 (OAI)
Available from: 2008-09-30 Created: 2008-09-30 Last updated: 2018-01-12Bibliographically approved
5. Multi-Attribute Decision Tree Evaluation in Imprecise and Uncertain Domains
Open this publication in new window or tab >>Multi-Attribute Decision Tree Evaluation in Imprecise and Uncertain Domains
2004 (English)In: Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference, Miami Beach, Florida, USA, Menlo Park: AAAI Press , 2004, p. 850-855Conference paper, Published paper (Other scientific)
Abstract [en]

We present a decision tree evaluation method integrated with a common framework for analyzing multi-attribute decisions under risk, where information is numerically imprecise. The approach extends the use of additive and multiplicative utility functions for supporting evaluation of imprecise statements, relaxing requirements for precise estimates of decision parameters. Information is modeled in convex sets of utility and probability measures restricted by closed intervals. Evaluation is done relative to a set of rules, generalizing the concept of admissibility, computationally handled through optimization of aggregated utility functions. Pros and cons of two approaches, and tradeoffs in selecting a utility function, are discussed.

Place, publisher, year, edition, pages
Menlo Park: AAAI Press, 2004
Keywords
Decision Analysis. Multiple Attributes, Imprecision
National Category
Computer Sciences
Identifiers
urn:nbn:se:miun:diva-2353 (URN)1688 (Local ID)1-57735-201-7 (ISBN)1688 (Archive number)1688 (OAI)
Available from: 2008-09-30 Created: 2008-09-30 Last updated: 2018-01-12Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records BETA

Johansson [Idefeldt], Jim

Search in DiVA

By author/editor
Johansson [Idefeldt], Jim
By organisation
Department of Information Technology and Media
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 965 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf