ray/rllib/tuned_examples/td3/mujoco-td3.yaml

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970 B
YAML

mujoco-td3:
# Solve latest versions of the four hardest Mujoco tasks benchmarked in the
# original TD3 paper. Average return over 10 trials at end of 1,000,000
# timesteps (taken from Table 2 of the paper) are given in parens at the end
# of reach environment name.
#
# Paper is at https://arxiv.org/pdf/1802.09477.pdf
env:
grid_search:
- HalfCheetah-v2 # (9,532.99)
- Hopper-v2 # (3,304.75)
- Walker2d-v2 # (4,565.24)
- Ant-v2 # (4,185.06)
run: TD3
stop:
timesteps_total: 1000000
config:
# Works for both torch and tf.
framework: tf
# === Exploration ===
exploration_config:
random_timesteps: 10000
replay_buffer_config:
type: MultiAgentReplayBuffer
num_steps_sampled_before_learning_starts: 10000
# === Evaluation ===
evaluation_interval: 10
evaluation_duration: 10