Making Confident Decisions with Model Ensembles.
Many policy decisions take input from collections of scientific models. Such decisions face significant and often poorly understood uncertainty. We rework the so-called confidence approach to tackle decision-making under severe uncertainty with multiple models, and we illustrate the approach with a...
| Publicado en: | Philosophy of Science Vol. 88; no. 3; pp. 439 - 461 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Cambridge University Press
Jul2021
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | Many policy decisions take input from collections of scientific models. Such decisions face significant and often poorly understood uncertainty. We rework the so-called confidence approach to tackle decision-making under severe uncertainty with multiple models, and we illustrate the approach with a case study: insurance pricing using hurricane models. The confidence approach has important consequences for this case and offers a powerful framework for a wide class of problems. We end by discussing different ways in which model ensembles can feed information into the approach, appropriate to different collections of models. |
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