This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 3 with difficulty 5 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 3
Difficulty: 5
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
    0.10000000298023223 +/- 0.14709666274350333
  • Extinguishing Trees on hivex-aerial-wildfire-suppression
    self-reported
    21.849999871850013 +/- 26.55595966139508
  • Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    109.25000078678131 +/- 132.77980124383632
  • Fire Out on hivex-aerial-wildfire-suppression
    self-reported
    0.2833333373069763 +/- 0.3903065252105535
  • 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
    720.8999999046325 +/- 714.1611892677554
  • Preparing Trees Reward on hivex-aerial-wildfire-suppression
    self-reported
    720.8999999046325 +/- 714.1611892677554
  • Water Drop on hivex-aerial-wildfire-suppression
    self-reported
    43.80000042915344 +/- 23.772717959813576
  • Water Pickup on hivex-aerial-wildfire-suppression
    self-reported
    43.35833301544189 +/- 23.80096972956163
  • Cumulative Reward on hivex-aerial-wildfire-suppression
    self-reported
    972.7084733963013 +/- 771.3352656170343