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This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 4 with difficulty 8 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 4
Difficulty: 8
Algorithm: PPO
Episode Length: 3000
Training max_steps: 1800000
Testing max_steps: 180000

Train & Test Scripts
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Evaluation results

  • Crash Count on hivex-aerial-wildfire-suppression
    self-reported
    0.9925824165344238 +/- 0.02284823226393604
  • Extinguishing Trees on hivex-aerial-wildfire-suppression
    self-reported
    0.0949134185910225 +/- 0.27686598704684745
  • Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    0.4745671033859253 +/- 1.3843300000675678
  • Fire Out on hivex-aerial-wildfire-suppression
    self-reported
    0.00357142873108387 +/- 0.015971914838998697
  • Fire too Close to City on hivex-aerial-wildfire-suppression
    self-reported
    0.026685259863734247 +/- 0.042508034690655574
  • Preparing Trees on hivex-aerial-wildfire-suppression
    self-reported
    281.05667572021486 +/- 33.36053303432415
  • Preparing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    281.05667572021486 +/- 33.36053303432415
  • Water Drop on hivex-aerial-wildfire-suppression
    self-reported
    1.9489688873291016 +/- 0.2672890550666218
  • Water Pickup on hivex-aerial-wildfire-suppression
    self-reported
    1.9453974604606628 +/- 0.2713707685551629
  • Cumulative Reward on hivex-aerial-wildfire-suppression
    self-reported
    171.03001670837403 +/- 35.59643888706601