This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 1 with difficulty 4 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 1
Difficulty: 4
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-1-difficulty-4

Aerial Wildfire Suppression

Collection

90 items • Updated Mar 20, 2025

Paper for hivex-research/hivex-AWS-PPO-baseline-task-1-difficulty-4

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

0.00833333358168602 +/- 0.03726780073566347
Extinguishing Trees on hivex-aerial-wildfire-suppression
self-reported

15.225000095367431 +/- 25.73818226110129
Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
self-reported

761.2499908447265 +/- 1286.9091013360119
Fire Out on hivex-aerial-wildfire-suppression
self-reported

0.36666666716337204 +/- 0.4244018838665434
Fire too Close to City on hivex-aerial-wildfire-suppression
self-reported

0.925 +/- 0.24468024246479642
Preparing Trees on hivex-aerial-wildfire-suppression
self-reported

651.3250035211444 +/- 627.0399351081593
Preparing Trees Reward on hivex-aerial-wildfire-suppression
self-reported

651.3250035211444 +/- 627.0399351081593
Water Drop on hivex-aerial-wildfire-suppression
self-reported

46.266666889190674 +/- 26.519958404149136
Water Pickup on hivex-aerial-wildfire-suppression
self-reported

45.76666655540466 +/- 26.436529035148055
Cumulative Reward on hivex-aerial-wildfire-suppression
self-reported

1711.8633205413819 +/- 2423.7230528427467