Decideit 3.0: Software for Second-Order Based Decision Evaluations

Mats Danielson, Love Ekenberg, Aron Larsson
Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications, PMLR 103:121-124, 2019.

Abstract

In this paper, we discuss representation and evaluation in the DecideIT 3.0 decision tool which is based on a belief mass interpretation of the background information. The decision components are imprecise in terms of intervals and qualitative estimates and we emphasise how multiplicative and additive aggregations influence the resulting belief distribution over the expected values.

Cite this Paper


BibTeX
@InProceedings{pmlr-v103-danielson19a, title = {Decideit 3.0: Software for Second-Order Based Decision Evaluations}, author = {Danielson, Mats and Ekenberg, Love and Larsson, Aron}, booktitle = {Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications}, pages = {121--124}, year = {2019}, editor = {De Bock, Jasper and de Campos, Cassio P. and de Cooman, Gert and Quaeghebeur, Erik and Wheeler, Gregory}, volume = {103}, series = {Proceedings of Machine Learning Research}, month = {03--06 Jul}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v103/danielson19a/danielson19a.pdf}, url = {https://proceedings.mlr.press/v103/danielson19a.html}, abstract = {In this paper, we discuss representation and evaluation in the DecideIT 3.0 decision tool which is based on a belief mass interpretation of the background information. The decision components are imprecise in terms of intervals and qualitative estimates and we emphasise how multiplicative and additive aggregations influence the resulting belief distribution over the expected values.} }
Endnote
%0 Conference Paper %T Decideit 3.0: Software for Second-Order Based Decision Evaluations %A Mats Danielson %A Love Ekenberg %A Aron Larsson %B Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications %C Proceedings of Machine Learning Research %D 2019 %E Jasper De Bock %E Cassio P. de Campos %E Gert de Cooman %E Erik Quaeghebeur %E Gregory Wheeler %F pmlr-v103-danielson19a %I PMLR %P 121--124 %U https://proceedings.mlr.press/v103/danielson19a.html %V 103 %X In this paper, we discuss representation and evaluation in the DecideIT 3.0 decision tool which is based on a belief mass interpretation of the background information. The decision components are imprecise in terms of intervals and qualitative estimates and we emphasise how multiplicative and additive aggregations influence the resulting belief distribution over the expected values.
APA
Danielson, M., Ekenberg, L. & Larsson, A.. (2019). Decideit 3.0: Software for Second-Order Based Decision Evaluations. Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications, in Proceedings of Machine Learning Research 103:121-124 Available from https://proceedings.mlr.press/v103/danielson19a.html.

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