Direct policy search for robust multi-objective management of deeply uncertain socio-ecological tipping points
Direct policy search for robust multi-objective management of deeply uncertain socio-ecological tipping points
复制标题
直接政策搜索，对高度不确定的社会生态临界点进行稳健的多目标管理
DOI：
10.1016/j.envsoft.2017.02.017
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
K. Keller
中科院分区：
文献类型：
--
作者：
J. Quinn;P. Reed;K. Keller
管理社会生态系统是一项挑战，由相互竞争的社会目标、深刻的不确定性和潜在的不可逆转的临界点构成。一个经典的、说教性的例子是浅湖问题，在这个问题中，一个假设的湖泊上的城镇必须制定污染控制策略，以最大化其经济效益，同时最小化湖泊越过临界磷(P)阈值的可能性，超过这个阈值，它将不可逆转地过渡到富营养化状态。在这里，我们探索使用直接政策搜索（DPS）为城镇设计鲁棒的污染控制规则，该规则考虑了深度不确定的系统特征和冲突的目标。DPS的闭环控制公式提高了关键管理权衡的质量和鲁棒性，同时相对于开环控制策略显著降低了解决多目标污染控制问题的计算复杂度。这些见解表明，DPS是管理具有高度不确定临界点的社会生态系统的一个很有前途的工具。
Managing socio-ecological systems is a challenge wrought by competing societal objectives, deep uncertainties, and potentially irreversible tipping points. A classic, didactic example is the shallow lake problem in which a hypothetical town situated on a lake must develop pollution control strategies to maximize its economic benefits while minimizing the probability of the lake crossing a critical phosphorus (P) threshold, above which it irreversibly transitions into a eutrophic state. Here, we explore the use of direct policy search (DPS) to design robust pollution control rules for the town that account for deeply uncertain system characteristics and conflicting objectives. The closed loop control formulation of DPS improves the quality and robustness of key management tradeoffs, while dramatically reducing the computational complexity of solving the multi-objective pollution control problem relative to open loop control strategies. These insights suggest DPS is a promising tool for managing socio-ecological systems with deeply uncertain tipping points.