This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 2 with difficulty 1 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 2
Difficulty: 1
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-2-difficulty-1

Aerial Wildfire Suppression

Collection

90 items • Updated Mar 20, 2025

Paper for hivex-research/hivex-AWS-PPO-baseline-task-2-difficulty-1

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

0.10833333656191826 +/- 0.13545462085140364
Extinguishing Trees on hivex-aerial-wildfire-suppression
self-reported

12.764999979734421 +/- 20.904079059070074
Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
self-reported

63.82500011920929 +/- 104.52039570112963
Fire Out on hivex-aerial-wildfire-suppression
self-reported

0.46333333626389506 +/- 0.3753984235292453
Fire too Close to City on hivex-aerial-wildfire-suppression
self-reported

0.7550000011920929 +/- 0.37763111996880777
Preparing Trees on hivex-aerial-wildfire-suppression
self-reported

561.5350036621094 +/- 325.15177018123586
Preparing Trees Reward on hivex-aerial-wildfire-suppression
self-reported

2807.674984741211 +/- 1625.7588563088673
Water Drop on hivex-aerial-wildfire-suppression
self-reported

19.77666656970978 +/- 9.682256516548964
Water Pickup on hivex-aerial-wildfire-suppression
self-reported

19.191666650772095 +/- 9.573244118078943
Cumulative Reward on hivex-aerial-wildfire-suppression
self-reported

3287.165838623047 +/- 1376.9107350360173