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ray/rllib/tuned_examples/mountaincarcontinuous-apex-ddpg.yaml

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[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 90 reward within ~1.5-2.5m timesteps / ~150-250 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
mountaincarcontinuous-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: MountainCarContinuous-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: 90
config:
clip_rewards: False
num_workers: 16
[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
exploration_ou_noise_scale: 1.0
[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
n_step: 3
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
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