Parallel-Data-Based Social Evolution Modeling
2021-06-15分类号:C934
【部门】China University of Petroleum Qingdao Academy of Intelligent Industry State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Institute of National Security National Defense University
【摘要】Abnormal or drastic changes in the natural environment may lead to unexpected events, such as tsunamis and earthquakes, which are becoming a major threat to national economy. Currently, no effective assessment approach can deduce a situation and determine the optimal response strategy when a natural disaster occurs.In this study, we propose a social evolution modeling approach and construct a deduction model for self-playing,self-learning, and self-upgrading on the basis of the idea of parallel data and reinforcement learning. The proposed approach can evaluate the impact of an event, deduce the situation, and provide optimal strategies for decisionmaking. Taking the breakage of a submarine cable caused by earthquake as an example, we find that the proposed modeling approach can obtain a higher reward compared with other existing methods.
【关键词】paral el data reinforcement learning decision-making
【基金】supported by the National Natural Science Foundation of China (No. 62072469);; the National Key R&D Program of China (No. 2018YFE0116700);; the Shandong Provincial Natural Science Foundation (No. ZR2019MF049, Parallel Data Driven Fault Prediction under On
【所属期刊栏目】Tsinghua Science and Technology
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