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Atari Games On Atari 2600 Krull

评估指标

Score

评测结果

各个模型在此基准测试上的表现结果

模型名称
Score
Paper TitleRepository
Rainbow+SEER3277.5Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings
GDI-I397575GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning-
VPN15930Value Prediction Network
Prior hs6872.8Prioritized Experience Replay
NoisyNet-Dueling10754Noisy Networks for Exploration
Gorila6363.1Massively Parallel Methods for Deep Reinforcement Learning
Prior+Duel noop10374.4Dueling Network Architectures for Deep Reinforcement Learning
CGP9086.8Evolving simple programs for playing Atari games
Prior+Duel hs7658.6Deep Reinforcement Learning with Double Q-learning
A3C FF hs5560.0Asynchronous Methods for Deep Reinforcement Learning
Duel hs8051.6Dueling Network Architectures for Deep Reinforcement Learning
Duel noop11451.9Dueling Network Architectures for Deep Reinforcement Learning
Best Learner3371.5The Arcade Learning Environment: An Evaluation Platform for General Agents
DreamerV250061Mastering Atari with Discrete World Models
Persistent AL8689.81Increasing the Action Gap: New Operators for Reinforcement Learning
A3C LSTM hs5911.4Asynchronous Methods for Deep Reinforcement Learning
DQN noop8422.3Deep Reinforcement Learning with Double Q-learning
GDI-H3594540Generalized Data Distribution Iteration-
ASL DDQN10422.5Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity-
MuZero269358.27Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
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