Abstract：Cyber-Physical systems (CPS) are getting more and more popular. How to make the system automatically capture the changes of complex statuses and take proper actions responding to the changes is one of the key problems of CPS. Combining with the reinforcement learning algorithm, a novel self-decision algorithm of CPS based on similarity computation, called Similarity Computation Based on Reinforcement Learning Algorithm(SCBRLA), is proposed to solve this problem. In this algorithm, the features of both system and system targets are firstly extracted, and then the similarities of current system state and target states are computed. Based on the computation result, system takes corresponding actions and decides the execution order of those actions. The proposed algorithm can be well used to analyze strategies of system self-decision when it receives attacks. The simulation results show that the proposed algorithm can help systems realize self-decision, and it has faster response speed compared with traditional method.
周旺平，王国栋. 基于相似度计算的信息物理融合系统自决策研究*[J]. 模式识别与人工智能, 2014, 27(11): 970-976.
ZHOU Wang-Ping, WANG Guo-Dong. Study on Self-Decision of Cyber-Physical Systems Based on Similarity Computation. , 2014, 27(11): 970-976.
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