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Atari Games On Atari 2600 Amidar

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Results

Performance results of various models on this benchmark

Paper TitleRepository
Agent5729660.08Agent57: Outperforming the Atari Human Benchmark
R2D229321.4Recurrent Experience Replay in Distributed Reinforcement Learning-
MuZero28634.39Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Ape-X8659.2Distributed Prioritized Experience Replay
NoisyNet-Dueling3537Noisy Networks for Exploration
FQF3165.3Fully Parameterized Quantile Function for Distributional Reinforcement Learning
IQN2946Implicit Quantile Networks for Distributional Reinforcement Learning
DreamerV22577Mastering Atari with Discrete World Models
Duel noop2354.5Dueling Network Architectures for Deep Reinforcement Learning
Prior+Duel noop2296.8Dueling Network Architectures for Deep Reinforcement Learning
ASL DDQN2232.3Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity
Prior noop1838.9Prioritized Experience Replay
DDQN (tuned) noop1793.3Dueling Network Architectures for Deep Reinforcement Learning
C51 noop1735.0A Distributional Perspective on Reinforcement Learning
QR-DQN-11641Distributional Reinforcement Learning with Quantile Regression
Advantage Learning1557.43Increasing the Action Gap: New Operators for Reinforcement Learning
IMPALA (deep)1554.79IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Persistent AL1451.65Increasing the Action Gap: New Operators for Reinforcement Learning
GDI-I31442Generalized Data Distribution Iteration-
A2C + SIL1362Self-Imitation Learning
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