ray/rllib/tuned_examples/a2c/cartpole-a2c.yaml

cartpole-a2c:
    env: CartPole-v0
    run: A2C
    stop:
        episode_reward_mean: 150
        timesteps_total: 500000
    config:
        # Works for both torch and tf.
        framework: tf
        num_workers: 0
        lr: 0.001
[RLlib] Benchmark and regression test yaml cleanup and restructuring. (#8414) 2020-05-26 11:10:27 +02:00			`cartpole-a2c:`
[RLlib] IMPALA PyTorch (#8287) This PR adds an IMPALA PyTorch implementation. - adds compilation tests for LSTM and w/o LSTM. - adds learning test for CartPole. 2020-05-03 13:44:25 +02:00			`env: CartPole-v0`
[RLlib] Benchmark and regression test yaml cleanup and restructuring. (#8414) 2020-05-26 11:10:27 +02:00			`run: A2C`
[RLlib] IMPALA PyTorch (#8287) This PR adds an IMPALA PyTorch implementation. - adds compilation tests for LSTM and w/o LSTM. - adds learning test for CartPole. 2020-05-03 13:44:25 +02:00			`stop:`
			`episode_reward_mean: 150`
			`timesteps_total: 500000`
			`config:`
[RLlib] Benchmark and regression test yaml cleanup and restructuring. (#8414) 2020-05-26 11:10:27 +02:00			`# Works for both torch and tf.`
[RLlib] Auto-framework, retire `use_pytorch` in favor of `framework=...` (#8520) 2020-05-27 16:19:13 +02:00			`framework: tf`
[RLlib] Benchmark and regression test yaml cleanup and restructuring. (#8414) 2020-05-26 11:10:27 +02:00			`num_workers: 0`
			`lr: 0.001`