This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 1 with difficulty 6 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 1
Difficulty: 6
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
    0.15000000447034836 +/- 0.20160177895130083
  • Extinguishing Trees on hivex-aerial-wildfire-suppression
    self-reported
    21.208333425223827 +/- 28.328527795039527
  • Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    1060.4166695594788 +/- 1416.426402849315
  • Fire Out on hivex-aerial-wildfire-suppression
    self-reported
    0.17500000223517417 +/- 0.2885484972637629
  • Fire too Close to City on hivex-aerial-wildfire-suppression
    self-reported
    0.9 +/- 0.26157418189029846
  • Preparing Trees on hivex-aerial-wildfire-suppression
    self-reported
    620.0166644275189 +/- 644.0197330961348
  • Preparing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    620.0166644275189 +/- 644.0197330961348
  • Water Drop on hivex-aerial-wildfire-suppression
    self-reported
    48.40833265781403 +/- 37.70947155566527
  • Water Pickup on hivex-aerial-wildfire-suppression
    self-reported
    48.12500007152558 +/- 37.613333288243446
  • Cumulative Reward on hivex-aerial-wildfire-suppression
    self-reported
    1735.4933523178101 +/- 1718.2560586121042