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Atari Games On Atari 2600 Yars Revenge

Metrics

Score

Results

Performance results of various models on this benchmark

Model Name
Score
Paper TitleRepository
QR-DQN-126447Distributional Reinforcement Learning with Quantile Regression
ASL DDQN29231.9Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity-
R2D2995048.4Recurrent Experience Replay in Distributed Reinforcement Learning-
MuZero553311.46Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Advantage Learning24240.03Increasing the Action Gap: New Operators for Reinforcement Learning
CGP28838.2Evolving simple programs for playing Atari games
Ape-X148594.8Distributed Prioritized Experience Replay
DNA564513DNA: Proximal Policy Optimization with a Dual Network Architecture
DreamerV2156748Mastering Atari with Discrete World Models
IMPALA (deep)84231.14IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
RUDDER60577RUDDER: Return Decomposition for Delayed Rewards
NoisyNet-Dueling86101Noisy Networks for Exploration
GDI-H3968090Generalized Data Distribution Iteration-
GDI-I3972000Generalized Data Distribution Iteration-
MuZero (Res2 Adam)219838.09Online and Offline Reinforcement Learning by Planning with a Learned Model
IQN28379Implicit Quantile Networks for Distributional Reinforcement Learning
Agent57998532.37Agent57: Outperforming the Atari Human Benchmark
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Atari Games On Atari 2600 Yars Revenge | SOTA | HyperAI