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Atari Games 벤치마크

Atari Games on Atari 2600 Atlantis

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Score

6.269e+04 1.006e+06 1.95e+06 2.894e+06 3.837e+06 2012-07 2026-11 UCT — 193858.0 (2012-07-19) Best Learner — 62687.0 (2012-07-19) UCT — 193858.0 (2012-07-19) Best Learner — 62687.0 (2012-07-19) Nature DQN — 85641.0 (2015-02-25) Nature DQN — 85641.0 (2015-02-25) Gorila — 629166.5 (2015-07-15) Gorila — 629166.5 (2015-07-15) Prior+Duel hs — 423252.0 (2015-09-22) DDQN (tuned) hs — 319688.0 (2015-09-22) DQN hs — 292491.0 (2015-09-22) DQN noop — 279987.0 (2015-09-22) Prior+Duel hs — 423252.0 (2015-09-22) DDQN (tuned) hs — 319688.0 (2015-09-22) DQN hs — 292491.0 (2015-09-22) DQN noop — 279987.0 (2015-09-22) Prior noop — 357324.0 (2015-11-18) Prior hs — 330647.0 (2015-11-18) Prior noop — 357324.0 (2015-11-18) Prior hs — 330647.0 (2015-11-18) Duel hs — 445360.0 (2015-11-20) Prior+Duel noop — 395762.0 (2015-11-20) Duel noop — 382572.0 (2015-11-20) DDQN (tuned) noop — 106056.0 (2015-11-20) Duel hs — 445360.0 (2015-11-20) Prior+Duel noop — 395762.0 (2015-11-20) Duel noop — 382572.0 (2015-11-20) DDQN (tuned) noop — 106056.0 (2015-11-20) Persistent AL — 1465250.0 (2015-12-15) Advantage Learning — 553591.67 (2015-12-15) Persistent AL — 1465250.0 (2015-12-15) Advantage Learning — 553591.67 (2015-12-15) A3C FF hs — 911091.0 (2016-02-04) A3C LSTM hs — 875822.0 (2016-02-04) A3C FF (1 day) hs — 772392.0 (2016-02-04) A3C FF hs — 911091.0 (2016-02-04) A3C LSTM hs — 875822.0 (2016-02-04) A3C FF (1 day) hs — 772392.0 (2016-02-04) Bootstrapped DQN — 994500.0 (2016-02-15) Bootstrapped DQN — 994500.0 (2016-02-15) DDQN+Pop-Art noop — 340076.0 (2016-02-24) DDQN+Pop-Art noop — 340076.0 (2016-02-24) ES FF (1 hour) noop — 1267410.0 (2017-03-10) ES FF (1 hour) noop — 1267410.0 (2017-03-10) Reactor 500M — 302831.0 (2017-04-15) Reactor 500M — 302831.0 (2017-04-15) NoisyNet-Dueling — 972175.0 (2017-06-30) NoisyNet-Dueling — 972175.0 (2017-06-30) C51 noop — 841075.0 (2017-07-21) C51 noop — 841075.0 (2017-07-21) QR-DQN-1 — 971850.0 (2017-10-27) QR-DQN-1 — 971850.0 (2017-10-27) IMPALA (deep) — 849967.5 (2018-02-05) IMPALA (deep) — 849967.5 (2018-02-05) Ape-X — 944497.5 (2018-03-02) Ape-X — 944497.5 (2018-03-02) A2C + SIL — 3084781.7 (2018-06-14) IQN — 978200.0 (2018-06-14) CGP — 99240.0 (2018-06-14) A2C + SIL — 3084781.7 (2018-06-14) IQN — 978200.0 (2018-06-14) CGP — 99240.0 (2018-06-14) POP3D — 2193605.67 (2018-07-02) POP3D — 2193605.67 (2018-07-02) R2D2 — 1620764.0 (2019-05-01) R2D2 — 1620764.0 (2019-05-01) MuZero — 1674767.2 (2019-11-19) MuZero — 1674767.2 (2019-11-19) Agent57 — 1528841.76 (2020-03-30) Agent57 — 1528841.76 (2020-03-30) DreamerV2 — 978778.0 (2020-10-05) DreamerV2 — 978778.0 (2020-10-05) MuZero (Res2 Adam) — 1137475.12 (2021-04-13) MuZero (Res2 Adam) — 1137475.12 (2021-04-13) GDI-H3 — 3837300.0 (2022-06-07) GDI-I3 — 3803000.0 (2022-06-07) GDI-H3 — 3837300.0 (2022-06-07) GDI-I3 — 3803000.0 (2022-06-07) DNA — 932559.0 (2022-06-20) DNA — 932559.0 (2022-06-20) ASL DDQN — 947275.0 (2023-05-07) ASL DDQN — 947275.0 (2023-05-07) UCT — 193858.0 (2012-07-19) Gorila — 629166.5 (2015-07-15) Persistent AL — 1465250.0 (2015-12-15) A2C + SIL — 3084781.7 (2018-06-14) GDI-H3 — 3837300.0 (2022-06-07)
RankModel Score PaperCodeYear
1 GDI-H3 3837300 Generalized Data Distribution Iteration 2022
2 GDI-I3 3803000 Generalized Data Distribution Iteration 2022
3 A2C + SIL 3084781.7 Self-Imitation Learning junhyukoh/self-imitation-learning · rwightman/pytorch-opensim-rl · SeungeonBaek/continuous-agents-test · +1 2018
4 POP3D 2193605.67 Policy Optimization With Penalized Point Probability Distance: An Alternative To Proximal Policy Optimization cxxgtxy/POP3D · paperwithcode/pop3d 2018
5 MuZero 1674767.20 Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model werner-duvaud/muzero-general · opendilab/LightZero · koulanurag/muzero-pytorch · +15 2019
6 R2D2 1620764.0 Recurrent Experience Replay in Distributed Reinforcement Learning opendilab/DI-engine · michaelnny/deep_rl_zoo · garymm/earl 2019
7 Agent57 1528841.76 Agent57: Outperforming the Atari Human Benchmark michaelnny/deep_rl_zoo · pocokhc/agent57 · yuta0821/agent57_pytorch · +2 2020
8 Persistent AL 1465250 Increasing the Action Gap: New Operators for Reinforcement Learning janhuenermann/neurojs · chainer/chainerrl 2015
9 ES FF (1 hour) noop 1267410.0 Evolution Strategies as a Scalable Alternative to Reinforcement Learning ray-project/ray · openai/evolution-strategies-starter · atgambardella/pytorch-es · +20 2017
10 MuZero (Res2 Adam) 1137475.12 Online and Offline Reinforcement Learning by Planning with a Learned Model DHDev0/Muzero-unplugged · enpasos/muzero 2021
11 Bootstrapped DQN 994500 Deep Exploration via Bootstrapped DQN tensorflow/models · tensorflow/models · NervanaSystems/coach · +3 2016
12 DreamerV2 978778 Mastering Atari with Discrete World Models opendilab/DI-engine · danijar/dreamerv2 · andrejorsula/drl_grasping · +6 2020
13 IQN 978200 Implicit Quantile Networks for Distributional Reinforcement Learning opendilab/DI-engine · chainer/chainerrl · Kchu/DeepRL_CK · +16 2018
14 NoisyNet-Dueling 972175 Noisy Networks for Exploration opendilab/DI-engine · Curt-Park/rainbow-is-all-you-need · chainer/chainerrl · +12 2017
15 QR-DQN-1 971850 Distributional Reinforcement Learning with Quantile Regression DLR-RM/stable-baselines3 · facebookresearch/Horizon · facebookresearch/ReAgent · +14 2017
16 ASL DDQN 947275 Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity xinjinghao/color 2023
17 Ape-X 944497.5 Distributed Prioritized Experience Replay ray-project/ray · vwxyzjn/cleanrl · opendilab/DI-engine · +12 2018
18 DNA 932559 DNA: Proximal Policy Optimization with a Dual Network Architecture maitchison/PPO 2022
19 A3C FF hs 911091.0 Asynchronous Methods for Deep Reinforcement Learning ray-project/ray · DLR-RM/stable-baselines3 · tensorpack/tensorpack · +67 2016
20 A3C LSTM hs 875822.0 Asynchronous Methods for Deep Reinforcement Learning ray-project/ray · DLR-RM/stable-baselines3 · tensorpack/tensorpack · +67 2016
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