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Atari Games On Atari 2600 River Raid

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Performance results of various models on this benchmark

Paper Title
MuZero323417.18Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
MuZero (Res2 Adam)171673.78Online and Offline Reinforcement Learning by Planning with a Learned Model
Ape-X63864.4Distributed Prioritized Experience Replay
Agent5763318.67Agent57: Outperforming the Atari Human Benchmark
R2D245632.1Recurrent Experience Replay in Distributed Reinforcement Learning
IMPALA (deep)29608.05IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
GDI-H328349Generalized Data Distribution Iteration
GDI-I328075Generalized Data Distribution Iteration
ASL DDQN24445Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity
FQF23560.7Fully Parameterized Quantile Function for Distributional Reinforcement Learning
Duel noop21162.6Dueling Network Architectures for Deep Reinforcement Learning
Prior+Duel noop20607.6Dueling Network Architectures for Deep Reinforcement Learning
IQN17765Implicit Quantile Networks for Distributional Reinforcement Learning
QR-DQN-117571Distributional Reinforcement Learning with Quantile Regression
C51 noop17322.0A Distributional Perspective on Reinforcement Learning
DNA16789DNA: Proximal Policy Optimization with a Dual Network Architecture
Duel hs16569.4Dueling Network Architectures for Deep Reinforcement Learning
Prior+Duel hs16496.8Deep Reinforcement Learning with Double Q-learning
DreamerV216351Mastering Atari with Discrete World Models
DDQN (tuned) noop14884.5Dueling Network Architectures for Deep Reinforcement Learning
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Atari Games On Atari 2600 River Raid | SOTA | HyperAI