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A hybrid intelligent control system model which combines high-level time Petri net (HLTPN) and Reinforcement Learning (RL) is proposed. In this model, the control system is modeled by HLTPN and system state last time is presented as transitions delay time. For optimizing the transition delay time through learning, a value item is appended to delay time of transition for recording the reward from environment...
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