Edit model card

This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 4 with difficulty 10 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 4
Difficulty: 10
Algorithm: PPO
Episode Length: 3000
Training max_steps: 1800000
Testing max_steps: 180000

Train & Test Scripts
Download the Environment

Downloads last month

-

Downloads are not tracked for this model. How to track
Video Preview
loading

Evaluation results

  • Crash Count on hivex-aerial-wildfire-suppression
    self-reported
    0.9949999988079071 +/- 0.022360685106199443
  • Extinguishing Trees on hivex-aerial-wildfire-suppression
    self-reported
    0.29754857206717134 +/- 0.6612722591280618
  • Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    1.4877428144216538 +/- 3.3063611877410133
  • Fire too Close to City on hivex-aerial-wildfire-suppression
    self-reported
    0.022103730216622354 +/- 0.039482863821780616
  • Preparing Trees on hivex-aerial-wildfire-suppression
    self-reported
    274.65237579345705 +/- 34.49504850001327
  • Preparing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    274.65237579345705 +/- 34.49504850001327
  • Water Drop on hivex-aerial-wildfire-suppression
    self-reported
    2.101252889633179 +/- 0.3808157213259622
  • Water Pickup on hivex-aerial-wildfire-suppression
    self-reported
    2.101252889633179 +/- 0.3808157213259622
  • Cumulative Reward on hivex-aerial-wildfire-suppression
    self-reported
    168.44546432495116 +/- 38.14918935961842