Deep Learning/강화학습 (18) 썸네일형 리스트형 [2018.11] Recurrent experience replay in distributed reinforcement learning Experience replay, increasing the data efficiency by stacking a fixed number of consecutive frames to overcome the partial observability in Atari 2600 games. However, with progress towards increasingly difficult, such as partially observable markov decision processes (POMDP), the need for more advanced memory-based representations increases, more principled solutions such as recurrent neural net.. [2017.07] Hindsight Experience Replay Dealing with sparse rewards is one of the biggest challenges in Reinforcement Learning (RL). We present a novel technique called Hindsight Experience Replay which allows sample-efficient learning from rewards which are sparse nd binary and therefore avoid the need for complicated reward engineering. It can be combined with an arbitrary off-policy RL algorithm and may be seen as a form of implici.. 이전 1 2 3 다음
