This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 1 with difficulty 8 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 1
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
    0.30833334252238276 +/- 0.2771777226968141
  • Extinguishing Trees on hivex-aerial-wildfire-suppression
    self-reported
    28.216666746139527 +/- 38.8679015625057
  • Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    1410.833318901062 +/- 1943.3950349162335
  • Fire Out on hivex-aerial-wildfire-suppression
    self-reported
    0.06666666865348816 +/- 0.16578715799245552
  • Fire too Close to City on hivex-aerial-wildfire-suppression
    self-reported
    0.975 +/- 0.11180339887498947
  • Preparing Trees on hivex-aerial-wildfire-suppression
    self-reported
    592.4916698455811 +/- 571.7471548283543
  • Preparing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    592.4916698455811 +/- 571.7471548283543
  • Water Drop on hivex-aerial-wildfire-suppression
    self-reported
    45.858332777023314 +/- 19.358443427747147
  • Water Pickup on hivex-aerial-wildfire-suppression
    self-reported
    45.541666460037234 +/- 19.38731633910842
  • Cumulative Reward on hivex-aerial-wildfire-suppression
    self-reported
    1881.6991638183595 +/- 1414.2531270122881