This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 4 with difficulty 7 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Aerial Wildfire Suppression
Task: 4
Difficulty: 7
Algorithm: PPO
Episode Length: 3000
Training max_steps: 1800000
Testing max_steps: 180000
Train & Test Scripts
Download the Environment
Evaluation results
- Crash Count on hivex-aerial-wildfire-suppressionself-reported0.996428570151329 +/- 0.015971919837000092
- Extinguishing Trees on hivex-aerial-wildfire-suppressionself-reported0.5590403918176889 +/- 2.1770827274580227
- Extinguishing Trees Reward on hivex-aerial-wildfire-suppressionself-reported2.7952019572257996 +/- 10.88541363667466
- Fire too Close to City on hivex-aerial-wildfire-suppressionself-reported0.010128205269575119 +/- 0.031176732946782266
- Preparing Trees on hivex-aerial-wildfire-suppressionself-reported289.3235092163086 +/- 35.916303930832015
- Preparing Trees Reward on hivex-aerial-wildfire-suppressionself-reported289.3235092163086 +/- 35.916303930832015
- Water Drop on hivex-aerial-wildfire-suppressionself-reported1.8651554942131043 +/- 0.2548557205509962
- Water Pickup on hivex-aerial-wildfire-suppressionself-reported1.8651554942131043 +/- 0.2548557205509962
- Cumulative Reward on hivex-aerial-wildfire-suppressionself-reported189.838374710083 +/- 30.620179554518494