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Bayesian policy support for adaptive strategies using computer models for complex physical systems / D. Williamson in Journal of the operational research society (JORS), Vol. 63 N° 8 (Août 2012) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 63 N° 8 (Août 2012) . - pp. 1021–1033 Titre : Bayesian policy support for adaptive strategies using computer models for complex physical systems Type de document : texte imprimé Auteurs : D. Williamson, Auteur ; M. Goldstein, Auteur Année de publication : 2012 Article en page(s) : pp. 1021–1033 Note générale : Operational research Langues : Anglais (eng) Mots-clés : Dynamic  programming  Policy  support  Sequential  emulation  Computer  models  Bayes  linear  adjustment  CO2  abatement Index. décimale : 001.424 Résumé : In this paper, we discuss combining expert knowledge and computer simulators in order to provide decision support for policy makers managing complex physical systems. We allow future states of the complex system to be viewed after initial policy is made, and for those states to influence revision of policy. The potential for future observations and intervention impacts heavily on optimal policy for today and this is handled within our approach. We show how deriving policy dependent system uncertainty using computer models leads to an intractable backwards induction problem for the resulting decision tree. We introduce an algorithm for emulating an upper bound on our expected loss surface for all possible policies and discuss how this might be used in policy support. To illustrate our methodology, we look at choosing an optimal CO2 abatement strategy, combining an intermediate complexity climate model and an economic utility model with climate data. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n8/abs/jors2011110a.html [article] Bayesian policy support for adaptive strategies using computer models for complex physical systems [texte imprimé] / D. Williamson, Auteur ; M. Goldstein, Auteur . - 2012 . - pp. 1021–1033. Operational research Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 63 N° 8 (Août 2012) . - pp. 1021–1033 Mots-clés : Dynamic  programming  Policy  support  Sequential  emulation  Computer  models  Bayes  linear  adjustment  CO2  abatement Index. décimale : 001.424 Résumé : In this paper, we discuss combining expert knowledge and computer simulators in order to provide decision support for policy makers managing complex physical systems. We allow future states of the complex system to be viewed after initial policy is made, and for those states to influence revision of policy. The potential for future observations and intervention impacts heavily on optimal policy for today and this is handled within our approach. We show how deriving policy dependent system uncertainty using computer models leads to an intractable backwards induction problem for the resulting decision tree. We introduce an algorithm for emulating an upper bound on our expected loss surface for all possible policies and discuss how this might be used in policy support. To illustrate our methodology, we look at choosing an optimal CO2 abatement strategy, combining an intermediate complexity climate model and an economic utility model with climate data. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n8/abs/jors2011110a.html