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https://github.com/vale981/ray
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38 lines
1.2 KiB
YAML
38 lines
1.2 KiB
YAML
# Given a SAC-generated offline file generated via:
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# rllib train -f tuned_examples/sac/pendulum-sac.yaml --no-ray-ui
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# Pendulum CQL can attain ~ -300 reward in 10k from that file.
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pendulum-cql:
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env: Pendulum-v1
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run: CQL
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stop:
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evaluation/episode_reward_mean: -700
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timesteps_total: 200000
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config:
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# Works for both torch and tf.
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framework: tf
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# Use one or more offline files or "input: sampler" for online learning.
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input: ["tests/data/pendulum/enormous.zip"]
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# Our input file above comes from an SAC run. Actions in there
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# are already normalized (produced by SquashedGaussian).
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actions_in_input_normalized: true
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clip_actions: true
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twin_q: true
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train_batch_size: 2000
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replay_buffer_config:
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type: MultiAgentReplayBuffer
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learning_starts: 0
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bc_iters: 100
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metrics_smoothing_episodes: 5
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# Evaluate in an actual environment.
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evaluation_interval: 1
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evaluation_num_workers: 2
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evaluation_num_episodes: 10
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evaluation_parallel_to_training: true
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evaluation_config:
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input: sampler
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explore: False
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