Bayesian policy support for adaptive strategies using computer models for complex physical systems

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.

[1]  A. Haurie,et al.  Coupling climate and economic models in a cost-benefit framework: A convex optimisation approach , 2006 .

[2]  Leon G. Higley,et al.  Forensic Entomology: An Introduction , 2009 .

[3]  A. O'Hagan,et al.  Bayesian calibration of computer models , 2001 .

[4]  J. Rougier.  Efficient Emulators for Multivariate Deterministic Functions , 2008 .

[5]  Nebojsa Nakicenovic,et al.  Avoiding dangerous climate change , 2006 .

[6]  Michael Goldstein,et al.  Bayesian Forecasting for Complex Systems Using Computer Simulators , 2001 .

[7]  Michael Goldstein,et al.  Reified Bayesian modelling and inference for physical systems , 2009 .

[8]  David Wooff,et al.  Bayes Linear Statistics , 2007 .

[9]  Robert Marsh,et al.  Uncertainties due to transport-parameter sensitivity in an efficient 3-D ocean-climate model , 2005 .

[10]  W. Nordhaus,et al.  Roll the DICE Again: Economic Models of Global Warming , 1999 .

[11]  T. J. Mitchell,et al.  Exploratory designs for computational experiments , 1995 .

[12]  Marian Leimbach,et al.  A modular approach to Integrated Assessment modeling , 2005 .

[13]  Jerome Sacks,et al.  Integrated circuit design optimization using a sequential strategy , 1992, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[14]  Michael Goldstein,et al.  Small Sample Bayesian Designs for Complex High-Dimensional Models Based on Information Gained Using Fast Approximations , 2009, Technometrics.

[15]  Jeremy E. Oakley,et al.  Decision-Theoretic Sensitivity Analysis for Complex Computer Models , 2009, Technometrics.

[16]  Sonja Kuhnt,et al.  Design and analysis of computer experiments , 2010 .

[17]  Jonathan Rougier,et al.  Analyzing the Climate Sensitivity of the HadSM3 Climate Model Using Ensembles from Different but Related Experiments , 2009 .

[18]  Adrian F. M. Smith,et al.  Bayesian Statistics 5. , 1998 .

[19]  David V. Budescu,et al.  Aided Decisions with Imprecise Probs 2 Aided and Unaided Decision Making With Imprecise Probabilities , 1978 .

[20]  Ian Vernon,et al.  Galaxy formation : a Bayesian uncertainty analysis. , 2010 .

[21]  Donald R. Jones,et al.  Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..

[22]  Jan Rotmans,et al.  Uncertainty in Integrated Assessment Modelling , 2002 .

[23]  J. Rougier,et al.  Bayes Linear Calibrated Prediction for Complex Systems , 2006 .

[24]  Klaus Keller,et al.  Avoiding Dangerous Anthropogenic Interference with the Climate System , 2005 .

[25]  David McInerney,et al.  Economically optimal risk reduction strategies in the face of uncertain climate thresholds , 2006 .

[26]  Robert J. Lempert,et al.  The Impacts of Climate Variability on Near-Term Policy Choices and the Value of Information , 2000 .

[27]  Daniel Williamson,et al.  Policy making using computer simulators for complex physical systems : Bayesian decision support for the development of adaptive strategies , 2010 .

[28]  Jan Rotmans,et al.  Integrated assessment: A growing child on its way to maturity , 1996 .

[29]  Igor Linkov,et al.  Model Uncertainty and Choices Made by Modelers: Lessons Learned from the International Atomic Energy Agency Model Intercomparisons † , 2003, Risk analysis : an official publication of the Society for Risk Analysis.

[30]  Richard J. T. Klein,et al.  Integrating mitigation and adaptation into climate and development policy: three research questions , 2005 .