mcu-uncertainty
Collection
Pretrained models for Microgrid Control Under Uncertainty. Repo: https://github.com/ahalev/Microgrid-Control-Under-Uncertainty
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49 items
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Updated
This model corresponds to run(s) in Table 2, specifically that with the hyperparameters:
1) {'scenario': 4, 'forecast_horizon': 6, 'intrinsic_reward_weight': 0.0001, 'bound_reward_weight': 'cosine', 'noise_std': 0.01}
from trainer import Trainer
trainer = Trainer.from_pretrained('ahalev/mcuu-table-2-mt790v35')
algo, env = trainer.algo, trainer.env
# Get an action from a random observation
action, _ = algo.policy.get_action(env.observation_space.sample())
# Evaluate the policy over 2920 timesteps
evaluation = trainer.evaluate()
For more information, see the repo and the paper.
This model was created by @ahalev.