Tsung-Kai Chao

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Reinforcement learning, a sub-area of machine learning, is a method of actively exploring feasible tactics and exploiting already known reward experiences in order to acquire a near-optimal policy. The Q-table of all state-action pairs forms the basis of policy of taking optimal action at each state. But an enormous amount of learning time is required for(More)
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