Computing Minimax Decisions with Incomplete Observations

Thijs van Ommen
Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, PMLR 62:358-369, 2017.

Abstract

Decision makers must often base their decisions on incomplete (coarse) data. Recent research has shown that in a wide variety of coarse data problems, minimax optimal strategies can be recognized using a simple probabilistic condition. This paper develops a computational method to find such strategies in special cases, and shows what difficulties may arise in more general cases.

Cite this Paper

BibTeX
@InProceedings{pmlr-v62-van ommen17a, title = {Computing Minimax Decisions with Incomplete Observations}, author = {van Ommen, Thijs}, booktitle = {Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications}, pages = {358--369}, year = {2017}, editor = {Antonucci, Alessandro and Corani, Giorgio and Couso, Inés and Destercke, Sébastien}, volume = {62}, series = {Proceedings of Machine Learning Research}, month = {10--14 Jul}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v62/van ommen17a/van ommen17a.pdf}, url = {https://proceedings.mlr.press/v62/van-ommen17a.html}, abstract = {Decision makers must often base their decisions on incomplete (coarse) data. Recent research has shown that in a wide variety of coarse data problems, minimax optimal strategies can be recognized using a simple probabilistic condition. This paper develops a computational method to find such strategies in special cases, and shows what difficulties may arise in more general cases.} }
Endnote
%0 Conference Paper %T Computing Minimax Decisions with Incomplete Observations %A Thijs van Ommen %B Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications %C Proceedings of Machine Learning Research %D 2017 %E Alessandro Antonucci %E Giorgio Corani %E Inés Couso %E Sébastien Destercke %F pmlr-v62-van ommen17a %I PMLR %P 358--369 %U https://proceedings.mlr.press/v62/van-ommen17a.html %V 62 %X Decision makers must often base their decisions on incomplete (coarse) data. Recent research has shown that in a wide variety of coarse data problems, minimax optimal strategies can be recognized using a simple probabilistic condition. This paper develops a computational method to find such strategies in special cases, and shows what difficulties may arise in more general cases.
APA
van Ommen, T.. (2017). Computing Minimax Decisions with Incomplete Observations. Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, in Proceedings of Machine Learning Research 62:358-369 Available from https://proceedings.mlr.press/v62/van-ommen17a.html.

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