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Adding restoration (#6)
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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

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Co-authored-by: Felipe Montealegre-Mora <[email protected]>
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felimomo and Felipe Montealegre-Mora committed Jun 6, 2024
1 parent d98cb6d commit b394d00
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45 changes: 40 additions & 5 deletions hyperpars/ppo-caribou.yml
Original file line number Diff line number Diff line change
@@ -1,12 +1,47 @@
# stable-baselines3 configuration

# 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"

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

# env
env_id: "CaribouScipy"
config: {}
n_envs: 12
tensorboard: "/home/rstudio/logs"
total_timesteps: 500000
use_sde: True
repo: "boettiger-lab/rl4eco"

# io
repo: "cboettig/rl-ecology"
save_path: "../saved_agents"
id: "2"

# misc
# id: ""
additional_imports: ["torch"]
47 changes: 41 additions & 6 deletions hyperpars/tqc-caribou.yml
Original file line number Diff line number Diff line change
@@ -1,12 +1,47 @@
# stable-baselines3 configuration

# 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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