This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 0 with difficulty 3 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 0
Difficulty: 3
Algorithm: PPO
Episode Length: 3000
Training max_steps: 1800000
Testing max_steps: 180000

Train & Test Scripts
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Reinforcement Learning

Collection including hivex-research/hivex-AWS-PPO-baseline-task-0-difficulty-3

Aerial Wildfire Suppression

Collection

90 items • Updated Mar 20, 2025

Paper for hivex-research/hivex-AWS-PPO-baseline-task-0-difficulty-3

HIVEX: A High-Impact Environment Suite for Multi-Agent Research (extended version)

Paper • 2501.04180 • Published Jan 7, 2025

Evaluation results

Crash Count on hivex-aerial-wildfire-suppression
self-reported

0.0833333358168602 +/- 0.12681432215480823
Extinguishing Trees on hivex-aerial-wildfire-suppression
self-reported

6.791666813194752 +/- 17.30909921307683
Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
self-reported

33.95833272337914 +/- 86.54549141729059
Fire Out on hivex-aerial-wildfire-suppression
self-reported

0.3250000037252903 +/- 0.372579912027151
Fire too Close to City on hivex-aerial-wildfire-suppression
self-reported

0.85 +/- 0.3284733426658932
Preparing Trees on hivex-aerial-wildfire-suppression
self-reported

1214.2916635513307 +/- 909.8089264585527
Preparing Trees Reward on hivex-aerial-wildfire-suppression
self-reported

1214.2916635513307 +/- 909.8089264585527
Water Drop on hivex-aerial-wildfire-suppression
self-reported

20.291666793823243 +/- 8.402323759531772
Water Pickup on hivex-aerial-wildfire-suppression
self-reported

19.79166646003723 +/- 8.33067930580936
Cumulative Reward on hivex-aerial-wildfire-suppression
self-reported

1321.465838623047 +/- 654.5775149733734