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* added restoration action to caribou scipy * parameter play, utility balancing, adding additive noise * params and init pop * notebook * new train fn * new hyperpar structure * three cosntant actions * four observations, rebalanced utility fn * noteboooks --------- Co-authored-by: Felipe Montealegre-Mora <[email protected]>
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# stable-baselines3 configuration | ||
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# algo: "PPO" | ||
# env_id: "CaribouScipy" | ||
# config: {} | ||
# n_envs: 12 | ||
# tensorboard: "../../../logs" | ||
# total_timesteps: 1000000 | ||
# use_sde: True | ||
# repo: "boettiger-lab/rl4eco" | ||
# save_path: "../saved_agents" | ||
# id: "3" | ||
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algo: "PPO" | ||
total_timesteps: 5000000 | ||
algo_config: | ||
tensorboard_log: "../../../logs" | ||
# | ||
policy: 'MlpPolicy' | ||
# batch_size: 512 | ||
# gamma: 0.9999 | ||
# learning_rate: !!float 7.77e-05 | ||
# ent_coef: 0.00429 | ||
# clip_range: 0.1 | ||
# gae_lambda: 0.9 | ||
# max_grad_norm: 5 | ||
# vf_coef: 0.19 | ||
# use_sde: True | ||
# policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" | ||
# in policy_kwargs: net_arch=[400, 300] | ||
# policy: 'MlpPolicy' | ||
# use_sde: True | ||
# policy_kwargs: "dict(log_std_init=-3, net_arch=[400, 300])" | ||
# clip_range: 0.1 | ||
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# env | ||
env_id: "CaribouScipy" | ||
config: {} | ||
n_envs: 12 | ||
tensorboard: "/home/rstudio/logs" | ||
total_timesteps: 500000 | ||
use_sde: True | ||
repo: "boettiger-lab/rl4eco" | ||
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# io | ||
repo: "cboettig/rl-ecology" | ||
save_path: "../saved_agents" | ||
id: "2" | ||
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# misc | ||
# id: "" | ||
additional_imports: ["torch"] |
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@@ -1,12 +1,47 @@ | ||
# stable-baselines3 configuration | ||
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||
# algo: "TQC" | ||
# env_id: "CaribouScipy" | ||
# n_envs: 12 | ||
# tensorboard: "/home/rstudio/logs" | ||
# total_timesteps: 500000 | ||
# config: {} | ||
# use_sde: True | ||
# repo: "boettiger-lab/rl4eco" | ||
# save_path: "../saved_agents" | ||
# id: "2" | ||
|
||
algo: "TQC" | ||
total_timesteps: 5000000 | ||
algo_config: | ||
tensorboard_log: "../../../logs" | ||
# | ||
policy: 'MlpPolicy' | ||
# batch_size: 512 | ||
# gamma: 0.9999 | ||
# learning_rate: !!float 7.77e-05 | ||
# ent_coef: 0.00429 | ||
# clip_range: 0.1 | ||
# gae_lambda: 0.9 | ||
# max_grad_norm: 5 | ||
# vf_coef: 0.19 | ||
# use_sde: True | ||
# policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" | ||
# in policy_kwargs: net_arch=[400, 300] | ||
# policy: 'MlpPolicy' | ||
# use_sde: True | ||
# policy_kwargs: "dict(log_std_init=-3, net_arch=[400, 300])" | ||
# clip_range: 0.1 | ||
|
||
# env | ||
env_id: "CaribouScipy" | ||
n_envs: 12 | ||
tensorboard: "/home/rstudio/logs" | ||
total_timesteps: 500000 | ||
config: {} | ||
use_sde: True | ||
repo: "boettiger-lab/rl4eco" | ||
n_envs: 12 | ||
|
||
# io | ||
repo: "cboettig/rl-ecology" | ||
save_path: "../saved_agents" | ||
id: "2" | ||
|
||
# misc | ||
# id: "" | ||
additional_imports: ["torch"] |
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