ray/rllib/tuned_examples/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-v0
    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_num_episodes: 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] 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			`env: Pendulum-v0`
[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`
			`evaluation_num_episodes: 10`