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This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 0 with difficulty 8 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 0
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
    0.10833333656191826 +/- 0.14584900099920892
  • Extinguishing Trees on hivex-aerial-wildfire-suppression
    self-reported
    23.324999898672104 +/- 55.08031019150775
  • Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    116.62500007152558 +/- 275.40155086604756
  • Fire Out on hivex-aerial-wildfire-suppression
    self-reported
    0.22500000149011612 +/- 0.3638448035924671
  • Fire too Close to City on hivex-aerial-wildfire-suppression
    self-reported
    0.85 +/- 0.28562028528873973
  • Preparing Trees on hivex-aerial-wildfire-suppression
    self-reported
    769.4333295822144 +/- 713.797537109146
  • Preparing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    769.4333295822144 +/- 713.797537109146
  • Water Drop on hivex-aerial-wildfire-suppression
    self-reported
    42.46666691303253 +/- 16.681099284118027
  • Water Pickup on hivex-aerial-wildfire-suppression
    self-reported
    42.0666668176651 +/- 16.62014604652166
  • Cumulative Reward on hivex-aerial-wildfire-suppression
    self-reported
    1093.1966667175293 +/- 733.5777441210589