ray/rllib/tuned_examples/sac/cartpole-continuous-pybullet-sac.yaml

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cartpole-sac:
env: CartPoleContinuousBulletEnv-v0
run: SAC
stop:
episode_reward_mean: 40
timesteps_total: 100000
config:
# Works for both torch and tf.
framework: tf
gamma: 0.95
no_done_at_end: false
horizon: 200
soft_horizon: true
n_step: 3
replay_buffer_config:
type: MultiAgentPrioritizedReplayBuffer
learning_starts: 256
initial_alpha: 0.2
clip_actions: false
min_sample_timesteps_per_iteration: 1000
optimization:
actor_learning_rate: 0.005
critic_learning_rate: 0.005
entropy_learning_rate: 0.0001