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https://github.com/vale981/ray
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f7e4dae852
* Add Atari SAC-discrete (learning MsPacman in 40k ts up to 780 rewards). * SAC loss function test case fix.
33 lines
994 B
YAML
33 lines
994 B
YAML
# Runs on a single g3.4xl node
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# See https://github.com/ray-project/rl-experiments for results
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atari-basic-dqn:
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env:
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grid_search:
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- BreakoutNoFrameskip-v4
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- BeamRiderNoFrameskip-v4
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- QbertNoFrameskip-v4
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- SpaceInvadersNoFrameskip-v4
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run: DQN
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config:
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double_q: false
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dueling: false
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num_atoms: 1
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noisy: false
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prioritized_replay: false
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n_step: 1
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target_network_update_freq: 8000
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lr: .0000625
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adam_epsilon: .00015
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hiddens: [512]
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learning_starts: 20000
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buffer_size: 1000000
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rollout_fragment_length: 4
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train_batch_size: 32
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exploration_config:
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epsilon_timesteps: 200000
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final_epsilon: 0.01
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prioritized_replay_alpha: 0.5
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final_prioritized_replay_beta: 1.0
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prioritized_replay_beta_annealing_timesteps: 2000000
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num_gpus: 0.2
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timesteps_per_iteration: 10000
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