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Atari Games On Atari 2600 Montezumas Revenge
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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
Columns
模型名称
Score
Paper Title
Repository
R2D2
2061.3
Recurrent Experience Replay in Distributed Reinforcement Learning
-
GDI-H3
2500
Generalized Data Distribution Iteration
-
Best Learner
10.7
The Arcade Learning Environment: An Evaluation Platform for General Agents
MP-EB
142
Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
Sarsa-φ-EB
2745.4
Count-Based Exploration in Feature Space for Reinforcement Learning
DNA
0
DNA: Proximal Policy Optimization with a Dual Network Architecture
DQN+SR
1778.8
Count-Based Exploration with the Successor Representation
A3C FF (1 day) hs
53
Asynchronous Methods for Deep Reinforcement Learning
IMPALA (deep)
0.00
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Prior+Duel hs
24.0
Deep Reinforcement Learning with Double Q-learning
A3C FF hs
67
Asynchronous Methods for Deep Reinforcement Learning
GDI-I3
3000
GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning
-
A2C+CoEX
6635
Contingency-Aware Exploration in Reinforcement Learning
-
Advantage Learning
0.42
Increasing the Action Gap: New Operators for Reinforcement Learning
POP3D
0
Policy Optimization With Penalized Point Probability Distance: An Alternative To Proximal Policy Optimization
Nature DQN
0
Human level control through deep reinforcement learning
DDQN-PC
3459
Unifying Count-Based Exploration and Intrinsic Motivation
ASL DDQN
0
Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity
-
Gorila
84
Massively Parallel Methods for Deep Reinforcement Learning
Sarsa-ε
399.5
Count-Based Exploration in Feature Space for Reinforcement Learning
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