REPRESENTING AND SOLVING ASYMMETRIC DECISION PROBLEMS
Thomas D. Nielsen () and
Finn V. Jensen ()
Additional contact information
Thomas D. Nielsen: Department of Computer Science, Aalborg University, Fredrik Bajers vej 7E, 9220 Aalborg ø, Denmark
Finn V. Jensen: Department of Computer Science, Aalborg University, Fredrik Bajers vej 7E, 9220 Aalborg ø, Denmark
International Journal of Information Technology & Decision Making (IJITDM), 2003, vol. 02, issue 02, 217-263
Abstract:
This paper deals with the representation and solution of asymmetric Bayesian decision problems. We present a formal framework, termedasymmetric influence diagrams. The framework is based on the syntax and semantics of the traditional influence diagram, and allows an efficient representation of asymmetric decision problems. As opposed to existing frameworks, the asymmetric influence diagram primarily encodes asymmetry at the qualitative level and it can therefore be read directly from the model.We give an algorithm for solving asymmetric influence diagrams. The algorithm initially decomposes the asymmetric decision problem into a structure of symmetric subproblems organized as a tree. A solution to the decision problem can then be found by propagating from the leaves towards the root using existing evaluation methods to solve the subproblems.
Keywords: Decision problems; asymmetry; influence diagrams; asymmetric influence diagrams; optimal strategy (search for similar items in EconPapers)
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219622003000604
Access to full text is restricted to subscribers
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijitdm:v:02:y:2003:i:02:n:s0219622003000604
Ordering information: This journal article can be ordered from
DOI: 10.1142/S0219622003000604
Access Statistics for this article
International Journal of Information Technology & Decision Making (IJITDM) is currently edited by Yong Shi
More articles in International Journal of Information Technology & Decision Making (IJITDM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().