New Methods for Decision-Focused Integrated Assessment: Multiple Objectives, Risk Evaluation and Visualization

约翰霍普金斯大学 该奖项是作为综合评估方法和模型竞赛的一部分颁发的。 它为研究人员提供资金，以开发将提高综合评估系统执行政策相关建模和决策评估的能力的方法，包括：（1）明确表示替代政策;（2）可靠的物理模型和/或容易修改系统以纳入替代模型结构和参数的能力;（3）解决系统决策者/用户关注的绩效指标或目标;（4）与模型输出相关的不确定性水平和来源的特征;（5）鼓励敏感性分析和探索并有效传达目标和不确定性之间的权衡的用户界面;以及（6）显示关于可接受风险和目标之间权衡的替代价值判断的含义的能力。 这些目标需要在三个研究领域进行研究。 研究的计算问题包括：（1）非支配方案的快速生成;（2）多目标时随机非支配方案的识别;（3）基于后悔准则的方案识别;（4）基于后悔准则的方案识别;（5）基于后悔准则的方案识别;（6）基于后悔准则的方案识别;（7）基于后悔准则的方案识别;（8）基于后悔准则的方案识别;（9）基于后悔准则的方案识别;（10）基于后悔准则的方案识别;（11）基于后悔准则的方案识别;（11）基于后悔准则的方案识别;（12）基于后悔准则的方案识别;（13）基于后悔准则的方案识别;（14）基于后悔准则的方案识别;（15）基于后悔准则的方案识别;（16）基于后悔准则的方案识别;（17）基于后悔准则的方案识别;（18）基于后悔准则的方案识别;（19）基于后悔准则的方案识别;（19）基于后悔准则的方案识别;（19）基于后悔准则的方案识别;（19）基于后悔准则的以及（4）将目标空间中的解决方案与决策空间中的相应解决方案联系起来的能力，以及选择该解决方案所隐含的价值判断，溶液 拟开发的可视化问题侧重于有效地展示关于权衡和风险的信息。 最后，对系统-用户动力学的研究将比较用户保存和比较结果的方法。 调查人员在这三个领域的工作将在一系列由该奖项支持的示范讲习班中进行测试。 这些研讨会将在实际的综合评估中使用新的建模和显示方法，以了解决策者如何使用新方法。 总的来说，这些改进应能增加政策建议的潜力，这些建议考虑到更全面的综合模式和可能的结果。

SBR-9634336 Ellis Hobbs Johns Hopkins University This award was made as part of the Methods and Models for Integrated Assessment competition. It provides funds for the investigators to develop methods that will improve the capability of integrated assessment systems to perform policy relevant modeling and decision evaluation by incorporating: (1) explicit representation of alternative policies; (2) credible physical models and/or the capability to easily modify the system to incorporate alternative model structures and parameters; (3) performance indicators or objectives that address the concerns of the policymaker/user of the system; (4) characterizations of the level and sources of uncertainty associated with model outputs; (5) a user interface that encourages sensitivity analysis and exploration and that effectively communicates tradeoffs among objectives and uncertainties; and (6) the ability to show the implications of alternative value judgments concerning acceptable risks and tradeoffs among objectives. These goals require research in three research areas. The computation issues that will be studied include: (1) rapid generation of nondominated alternatives; (2) identification of stochastically nondominated alternatives when there are multiple objectives; (3) identification of alternatives that perform well on regret-based criteria; and (4) the ability to link a solution in objective space with the corresponding solution in decision space and the value judgments implied by choosing that solution. The visualization issues to be developed focus on effective presentation of information on tradeoffs and risks. Finally, research into system-user dynamics will compare methods for users to save and compare results. The investigators' work in these three areas will be tested in a set of demonstration workshops that are supported by this award. These workshops will use the new modeling and display methods on actual integrated assessments, to see how policy-makers make use o f the new methods. Overall, these improvements should increase the potential for policy recommendations that consider a fuller range of integrated models and possible outcomes.