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SOTA
Atari-Spiele
Atari Games On Atari 2600 Robotank
Atari Games On Atari 2600 Robotank
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Score
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Score
Paper Title
MuZero
131.13
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Agent57
127.32
Agent57: Outperforming the Atari Human Benchmark
GDI-H3
113.4
Generalized Data Distribution Iteration
GDI-I3
108.2
Generalized Data Distribution Iteration
GDI-I3
108.2
GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning
MuZero (Res2 Adam)
100.59
Online and Offline Reinforcement Learning by Planning with a Learned Model
R2D2
100.4
Recurrent Experience Replay in Distributed Reinforcement Learning
DreamerV2
78
Mastering Atari with Discrete World Models
FQF
75.7
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
Ape-X
73.8
Distributed Prioritized Experience Replay
Advantage Learning
69.31
Increasing the Action Gap: New Operators for Reinforcement Learning
Bootstrapped DQN
66.6
Deep Exploration via Bootstrapped DQN
ASL DDQN
65.8
Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity
Duel noop
65.3
Dueling Network Architectures for Deep Reinforcement Learning
DDQN (tuned) noop
65.1
Dueling Network Architectures for Deep Reinforcement Learning
DNA
64.8
DNA: Proximal Policy Optimization with a Dual Network Architecture
DDQN+Pop-Art noop
64.3
Learning values across many orders of magnitude
NoisyNet-Dueling
64
Noisy Networks for Exploration
DQN noop
63.9
Deep Reinforcement Learning with Double Q-learning
Prior noop
62.6
Prioritized Experience Replay
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Atari Games On Atari 2600 Robotank | SOTA | HyperAI