ray/rllib/tuned_examples/regression_tests/pendulum-ddpg-tf.yaml

pendulum-ddpg-tf:
    env: Pendulum-v0
    run: DDPG
    stop:
        episode_reward_mean: -900
        timesteps_total: 100000
    config:
        use_pytorch: false
        use_huber: true
        clip_rewards: false
[RLlib] DDPG PyTorch version. (#7953) The DDPG/TD3 algorithms currently do not have a PyTorch implementation. This PR adds PyTorch support for DDPG/TD3 to RLlib. This PR: - Depends on the re-factor PR for DDPG (Functional Algorithm API). - Adds learning regression tests for the PyTorch version of DDPG and a DDPG (torch) - Updates the documentation to reflect that DDPG and TD3 now support PyTorch. * Learning Pendulum-v0 on torch version (same config as tf). Wall time a little slower (~20% than tf). * Fix GPU target model problem. 2020-04-16 10:20:01 +02:00			`pendulum-ddpg-tf:`
[RLLib] DDPG (#1685) 2018-04-11 15:08:39 -07:00			`env: Pendulum-v0`
			`run: DDPG`
			`stop:`
[rllib] Run simple regressions tests for all algs in jenkins (#3498) 2018-12-11 17:21:53 -08:00			`episode_reward_mean: -900`
			`timesteps_total: 100000`
[RLLib] DDPG (#1685) 2018-04-11 15:08:39 -07:00			`config:`
[RLlib] DDPG PyTorch version. (#7953) The DDPG/TD3 algorithms currently do not have a PyTorch implementation. This PR adds PyTorch support for DDPG/TD3 to RLlib. This PR: - Depends on the re-factor PR for DDPG (Functional Algorithm API). - Adds learning regression tests for the PyTorch version of DDPG and a DDPG (torch) - Updates the documentation to reflect that DDPG and TD3 now support PyTorch. * Learning Pendulum-v0 on torch version (same config as tf). Wall time a little slower (~20% than tf). * Fix GPU target model problem. 2020-04-16 10:20:01 +02:00			`use_pytorch: false`
			`use_huber: true`
			`clip_rewards: false`