Multi-currency Influence Diagrams
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Multi-currency Influence Diagrams. / Nielsen, Søren Holbech; Nielsen, Thomas Dyhre; Jensen, Finn V.
Advances in Probabilistic Graphical Models. ed. / Peter Lucas; José Gamez; Antonio Salmeron. Vol. 213 Springer, 2007. p. 275-294 (Studies in Fuzziness and Soft Computing, Vol. 213).Publication: Research › Book chapter
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TY - CHAP
T1 - Multi-currency Influence Diagrams
A1 - Nielsen,Søren Holbech
A1 - Nielsen,Thomas Dyhre
A1 - Jensen,Finn V.
AU - Nielsen,Søren Holbech
AU - Nielsen,Thomas Dyhre
AU - Jensen,Finn V.
PB - Springer
PY - 2007
Y1 - 2007
N2 - When using the influence diagrams framework for solving a decision problem with several different quantitative utilities, the traditional approach has been to convert the utilities into one common currency. This conversion is carried out using a tacit transformation, under the assumption that the converted problem is equivalent to the original one. In this paper we present an extension of the influence diagram framework. The extension allows for these decision problems to be modelled in their original form. We present an algorithm that, given a linear conversion function between the currencies of the original utilities, discovers a characterisation of all other such functions, which induce the same optimal strategy. As this characterisation can potentially be very complex, we give methods to present it in an approximate way.
AB - When using the influence diagrams framework for solving a decision problem with several different quantitative utilities, the traditional approach has been to convert the utilities into one common currency. This conversion is carried out using a tacit transformation, under the assumption that the converted problem is equivalent to the original one. In this paper we present an extension of the influence diagram framework. The extension allows for these decision problems to be modelled in their original form. We present an algorithm that, given a linear conversion function between the currencies of the original utilities, discovers a characterisation of all other such functions, which induce the same optimal strategy. As this characterisation can potentially be very complex, we give methods to present it in an approximate way.
KW - Decision Processes
KW - Inference
KW - Learning
KW - Probabilistic Graphical Models
SN - 978-3-540-68994-2
SN - 354068994X
VL - 213
BT - Advances in Probabilistic Graphical Models
T2 - Advances in Probabilistic Graphical Models
A2 - Salmeron,Antonio
ED - Salmeron,Antonio
T3 - Studies in Fuzziness and Soft Computing
T3 - en_GB
SP - 275
EP - 294
ER -