Q-learning is a typical Reinforcement Learning (RL) method with a slow convergence speed especially as the scales of the state space and action space increase.
学习是一种典型的强化学习，其学习效率较低，尤其是当状态空间和决策空间较大时。
The direct solution is a important method to solve the fuzzy optimum design for the symmetry type, but sometimes the speed is too slow and the precision is low in the convergence.
直接法是求解对称型模糊优化问题的一种重要方法，但实际计算中存在收敛速度过慢或收敛精度过低的问题。
Our previous work has shown that the network was effective in improving two difficulties, a convergence to local minimal and a slow learning speed.
并对以前神经网络中的两个难点：局部极小和收敛速度慢的问题进行分析。
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