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With the gradually stricter requirement for multimedia applications, spectrum inefficiencies are urgent to be relieved by sensing and utilizing Spectrum Holes (SHs) over a wide spectrum. Cognitive Radio Sensor Network (CRSN) has drawn a lot of attention, which determines the state of Primary Users (PUs) by implementing Cooperative Spectrum Sensing (CSS), further overcoming various noise and fading issues in the radio environment. A survey on the application of Reinforcement Learning (RL) technology for CSS is conducted, especially through handling the performance optimization problem that cannot be achieved by traditional methods. Specifically, we transformed the traditional Fusion Center (FC) into an intelligent Agent that is responsible for making fusion decisions based on the results of Energy Detection (ED) technology. In this way, through learning from experience, the system performance in global …