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从DQN到Double DQN:分离动作选择与价值评估,解决强化学习中的Q值过 ...
2015年DQN在Atari游戏上取得突破性进展,从此以后强化学习终于能处理复杂环境了,但没多久研究者就注意到一些奇怪的现象: Q值会莫名其妙地增长到很大,智能体变得异常自信,坚信某些动作价值极高。实际跑起来却发现这些"黄金动作"根本靠不住,部分游戏的 ...
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