This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 1 with difficulty 6 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 1
Difficulty: 6
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-6

Aerial Wildfire Suppression

Collection

90 items • Updated Mar 20, 2025

Paper for hivex-research/hivex-AWS-PPO-baseline-task-1-difficulty-6

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

0.15000000447034836 +/- 0.20160177895130083
Extinguishing Trees on hivex-aerial-wildfire-suppression
self-reported

21.208333425223827 +/- 28.328527795039527
Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
self-reported

1060.4166695594788 +/- 1416.426402849315
Fire Out on hivex-aerial-wildfire-suppression
self-reported

0.17500000223517417 +/- 0.2885484972637629
Fire too Close to City on hivex-aerial-wildfire-suppression
self-reported

0.9 +/- 0.26157418189029846
Preparing Trees on hivex-aerial-wildfire-suppression
self-reported

620.0166644275189 +/- 644.0197330961348
Preparing Trees Reward on hivex-aerial-wildfire-suppression
self-reported

620.0166644275189 +/- 644.0197330961348
Water Drop on hivex-aerial-wildfire-suppression
self-reported

48.40833265781403 +/- 37.70947155566527
Water Pickup on hivex-aerial-wildfire-suppression
self-reported

48.12500007152558 +/- 37.613333288243446
Cumulative Reward on hivex-aerial-wildfire-suppression
self-reported

1735.4933523178101 +/- 1718.2560586121042