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Discrete SAC benchmark update

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@kengz kengz released this 13 Nov 08:21
· 124 commits to master since this release
1b634c0

Discrete SAC benchmark update

Env. \ Alg. DQN DDQN+PER A2C (GAE) A2C (n-step) PPO SAC
Breakout
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80.88 182 377 398 443 3.51*
Pong
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18.48 20.5 19.31 19.56 20.58 19.87*
Seaquest
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1185 4405 1070 1684 1715 171*
Qbert
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5494 11426 12405 13590 13460 923*
LunarLander
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192 233 25.21 68.23 214 276
UnityHallway
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-0.32 0.27 0.08 -0.96 0.73 0.01
UnityPushBlock
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4.88 4.93 4.68 4.93 4.97 -0.70

Episode score at the end of training attained by SLM Lab implementations on discrete-action control problems. Reported episode scores are the average over the last 100 checkpoints, and then averaged over 4 Sessions. A Random baseline with score averaged over 100 episodes is included. Results marked with * were trained using the hybrid synchronous/asynchronous version of SAC to parallelize and speed up training time. For SAC, Breakout, Pong and Seaquest were trained for 2M frames instead of 10M frames.

For the full Atari benchmark, see Atari Benchmark