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SOTA
Atari Games
Atari Games On Atari 2600 Fishing Derby
Atari Games On Atari 2600 Fishing Derby
Métriques
Score
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
Score
Paper Title
Repository
IMPALA (deep)
44.85
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
FQF
52.7
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
Duel hs
-4.1
Dueling Network Architectures for Deep Reinforcement Learning
DDQN+Pop-Art noop
45.1
Learning values across many orders of magnitude
-
DQN noop
-4.9
Deep Reinforcement Learning with Double Q-learning
POP3D
28.99
Policy Optimization With Penalized Point Probability Distance: An Alternative To Proximal Policy Optimization
CGP
-51
Evolving simple programs for playing Atari games
Duel noop
46.4
Dueling Network Architectures for Deep Reinforcement Learning
GDI-I3
59
Generalized Data Distribution Iteration
-
NoisyNet-Dueling
57
Noisy Networks for Exploration
QR-DQN-1
39
Distributional Reinforcement Learning with Quantile Regression
Ape-X
44.4
Distributed Prioritized Experience Replay
Advantage Learning
21.32
Increasing the Action Gap: New Operators for Reinforcement Learning
Best Learner
-89.5
The Arcade Learning Environment: An Evaluation Platform for General Agents
Prior hs
9.8
Prioritized Experience Replay
DreamerV2
65
Mastering Atari with Discrete World Models
A2C + SIL
55.8
Self-Imitation Learning
IDVQ + DRSC + XNES
-10
Playing Atari with Six Neurons
R2D2
85.8
Recurrent Experience Replay in Distributed Reinforcement Learning
-
GDI-I3
59
GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning
-
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