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Atari Games On Atari 2600 Berzerk

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이 벤치마크에서 각 모델의 성능 결과

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Score
Paper TitleRepository
FQF12422.2Fully Parameterized Quantile Function for Distributional Reinforcement Learning
A3C FF (1 day) hs1433.4Asynchronous Methods for Deep Reinforcement Learning
Ape-X57196.7Distributed Prioritized Experience Replay
IQN1053Implicit Quantile Networks for Distributional Reinforcement Learning
DDQN+Pop-Art noop1199.6Learning values across many orders of magnitude-
DDQN (tuned) hs1011.1Deep Reinforcement Learning with Double Q-learning
A3C FF hs817.9Asynchronous Methods for Deep Reinforcement Learning
A3C LSTM hs862.2Asynchronous Methods for Deep Reinforcement Learning
ES FF (1 hour) noop686.0Evolution Strategies as a Scalable Alternative to Reinforcement Learning
Prior noop1305.6Prioritized Experience Replay
DQN noop585.6Deep Reinforcement Learning with Double Q-learning
GDI-I37607GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning-
Prior+Duel hs2178.6Deep Reinforcement Learning with Double Q-learning
Prior hs865.9Prioritized Experience Replay
IMPALA (deep)1852.70IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
C51 noop1645.0A Distributional Perspective on Reinforcement Learning
Reactor 500M2303.1The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning-
Agent5761507.83Agent57: Outperforming the Atari Human Benchmark
MuZero85932.60Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
DQN hs493.4Deep Reinforcement Learning with Double Q-learning
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