ray/rllib/tuned_examples/apex_ddpg/pendulum-apex-ddpg.yaml

# This can be expected to reach -160 reward within 2.5 timesteps / ~250 seconds on a K40 GPU
pendulum-apex-ddpg:
    env: Pendulum-v1
    run: APEX_DDPG
    stop:
        episode_reward_mean: -160
    config:
        # Works for both torch and tf.
        framework: tf
        use_huber: True
        clip_rewards: False
        num_workers: 16
        n_step: 1
        target_network_update_freq: 50000
        tau: 1.0
        evaluation_interval: 5
        evaluation_duration: 10
[rllib] Contribute DDPG to RLlib (#1877) * ongoing ddpg * ongoing ddpg converged * gpu machine changes * tuned * tuned ddpg specification * ddpg * supplement missed optimizer argument clip_rewards in default DQN configuration * ddpg supports vision env (atari) now * revised according to code review comments * added regression test case * removed irrelevant files * validate ddpg on mountain_car_continuous * restore unnecessary slight changes * revised according to eric's comments * added the requested tests * revised accordingly * revised accordingly and re-validated * formatted by yapf * fix lint errors * formatted by yapf * fix lint errors * formatted by yapf * fix lint error 2018-04-19 22:36:29 -07:00			`# This can be expected to reach -160 reward within 2.5 timesteps / ~250 seconds on a K40 GPU`
[rllib] Add DDPG documentation, rename DDPG2 <=> DDPG (#1946) * updates * updates * updates * updates * updates * updates * Update rllib.rst * Update policy-optimizers.rst 2018-04-30 00:18:15 -07:00			`pendulum-apex-ddpg:`
[RLlib] Upgrade gym version to 0.21 and deprecate pendulum-v0. (#19535) * Fix QMix, SAC, and MADDPA too. * Unpin gym and deprecate pendulum v0 Many tests in rllib depended on pendulum v0, however in gym 0.21, pendulum v0 was deprecated in favor of pendulum v1. This may change reward thresholds, so will have to potentially rerun all of the pendulum v1 benchmarks, or use another environment in favor. The same applies to frozen lake v0 and frozen lake v1 Lastly, all of the RLlib tests and have been moved to python 3.7 * Add gym installation based on python version. Pin python<= 3.6 to gym 0.19 due to install issues with atari roms in gym 0.20 * Reformatting * Fixing tests * Move atari-py install conditional to req.txt * migrate to new ale install method * Fix QMix, SAC, and MADDPA too. * Unpin gym and deprecate pendulum v0 Many tests in rllib depended on pendulum v0, however in gym 0.21, pendulum v0 was deprecated in favor of pendulum v1. This may change reward thresholds, so will have to potentially rerun all of the pendulum v1 benchmarks, or use another environment in favor. The same applies to frozen lake v0 and frozen lake v1 Lastly, all of the RLlib tests and have been moved to python 3.7 * Add gym installation based on python version. Pin python<= 3.6 to gym 0.19 due to install issues with atari roms in gym 0.20 Move atari-py install conditional to req.txt migrate to new ale install method Make parametric_actions_cartpole return float32 actions/obs Adding type conversions if obs/actions don't match space Add utils to make elements match gym space dtypes Co-authored-by: Jun Gong <jungong@anyscale.com> Co-authored-by: sven1977 <svenmika1977@gmail.com> 2021-11-03 08:24:00 -07:00			`env: Pendulum-v1`
[rllib] Add DDPG documentation, rename DDPG2 <=> DDPG (#1946) * updates * updates * updates * updates * updates * updates * Update rllib.rst * Update policy-optimizers.rst 2018-04-30 00:18:15 -07:00			`run: APEX_DDPG`
[rllib] Contribute DDPG to RLlib (#1877) * ongoing ddpg * ongoing ddpg converged * gpu machine changes * tuned * tuned ddpg specification * ddpg * supplement missed optimizer argument clip_rewards in default DQN configuration * ddpg supports vision env (atari) now * revised according to code review comments * added regression test case * removed irrelevant files * validate ddpg on mountain_car_continuous * restore unnecessary slight changes * revised according to eric's comments * added the requested tests * revised accordingly * revised accordingly and re-validated * formatted by yapf * fix lint errors * formatted by yapf * fix lint errors * formatted by yapf * fix lint error 2018-04-19 22:36:29 -07:00			`stop:`
			`episode_reward_mean: -160`
			`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] Contribute DDPG to RLlib (#1877) * ongoing ddpg * ongoing ddpg converged * gpu machine changes * tuned * tuned ddpg specification * ddpg * supplement missed optimizer argument clip_rewards in default DQN configuration * ddpg supports vision env (atari) now * revised according to code review comments * added regression test case * removed irrelevant files * validate ddpg on mountain_car_continuous * restore unnecessary slight changes * revised according to eric's comments * added the requested tests * revised accordingly * revised accordingly and re-validated * formatted by yapf * fix lint errors * formatted by yapf * fix lint errors * formatted by yapf * fix lint error 2018-04-19 22:36:29 -07:00			`use_huber: True`
			`clip_rewards: False`
			`num_workers: 16`
			`n_step: 1`
			`target_network_update_freq: 50000`
			`tau: 1.0`
[rllib] TD3/DDPG improvements and MuJoCo benchmarks (#4694) * [rllib] Separate optimisers for DDPG actor & crit. * [rllib] Better names for DDPG variables & options Config changes: - noise_scale -> exploration_ou_noise_scale - exploration_theta -> exploration_ou_theta - exploration_sigma -> exploration_ou_sigma - act_noise -> exploration_gaussian_sigma - noise_clip -> target_noise_clip * [rllib] Make DDPG less class-y Used functions to replace three classes with only an __init__ method & a handful of unrelated attributes. * [rllib] Refactor DDPG noise * [rllib] Unify DDPG exploration annealing Added option "exploration_should_anneal" to enable linear annealing of exploration noise. By default this is off, for consistency with DDPG & TD3 papers. Also renamed "exploration_final_eps" to "exploration_final_scale" (that name seems to have been carried over from DQN, and doesn't really make sense here). Finally, tried to rename "eps" to "noise_scale" wherever possible. 2019-04-26 17:49:53 -07:00			`evaluation_interval: 5`
[RLlib] Allow for evaluation to run by `timesteps` (alternative to `episodes`) and add auto-setting to make sure train doesn't ever have to wait for eval (e.g. long episodes) to finish. (#20757) 2021-12-04 13:26:33 +01:00			`evaluation_duration: 10`