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understand that correlated samples cause problem. and how paralled solve the problem
another solution is replay buffers, fully ultilizing the advantage of off policy in Q-learning.
there‘s still a problem: Q learning is not gradient descent
divide Q function into two parts: the target net and the evolving net.
sacrifice speed to get the convergence.
overestimation of Natural DQN
get trouble in left and right dilemma of avoiding bumping on a tree
CS294-112 深度强化学习 秋季学期（伯克利）NO.6 Value functions introduction NO.7 Advanced Q learning
原文：https://www.cnblogs.com/ecoflex/p/9094123.html