mirror of
https://github.com/wassname/ray.git
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andrewztan
1475600c81
* removed ddpg2 * removed ddpg2 from codebase * added tests used in ddpg vs ddpg2 comparison * added notes about training timesteps to yaml files * removed ddpg2 yaml files * removed unnecessary configs from yaml files * removed unnecessary configs from yaml files * moved pendulum, mountaincarcontinuous, and halfcheetah tests to tuned_examples * moved pendulum, mountaincarcontinuous, and halfcheetah tests to tuned_examples * added more configuration details to yaml files * removed random starts from halfcheetah
68 lines
1.8 KiB
YAML
68 lines
1.8 KiB
YAML
# This configuration can expect to reach -160 reward in 10k-20k timesteps
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pendulum-ddpg:
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env: Pendulum-v0
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run: DDPG
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stop:
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episode_reward_mean: -160
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time_total_s: 600 # 10 minutes
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config:
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# === Model ===
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actor_hiddens: [64, 64]
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critic_hiddens: [64, 64]
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n_step: 1
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model: {}
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gamma: 0.99
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env_config: {}
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# === Exploration ===
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schedule_max_timesteps: 100000
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timesteps_per_iteration: 600
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exploration_fraction: 0.1
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exploration_final_eps: 0.02
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noise_scale: 0.1
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exploration_theta: 0.15
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exploration_sigma: 0.2
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target_network_update_freq: 0
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tau: 0.001
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# === Replay buffer ===
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buffer_size: 10000
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prioritized_replay: True
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prioritized_replay_alpha: 0.6
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prioritized_replay_beta: 0.4
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prioritized_replay_eps: 0.000001
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clip_rewards: False
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# === Optimization ===
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actor_lr: 0.0001
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critic_lr: 0.001
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use_huber: True
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huber_threshold: 1.0
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l2_reg: 0.000001
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learning_starts: 500
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sample_batch_size: 1
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train_batch_size: 64
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smoothing_num_episodes: 10
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# === Tensorflow ===
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tf_session_args: {
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"device_count": {
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"CPU": 2
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},
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"log_device_placement": False,
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"allow_soft_placement": True,
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"gpu_options": {
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"allow_growth": True
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},
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"inter_op_parallelism_threads": 1,
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"intra_op_parallelism_threads": 1,
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}
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# === Parallelism ===
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num_workers: 0
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num_gpus_per_worker: 0
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optimizer_class: "LocalSyncReplayOptimizer"
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optimizer_config: {}
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per_worker_exploration: False
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worker_side_prioritization: False
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