This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 6 with difficulty 7 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 6
Difficulty: 7
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-6-difficulty-7

Aerial Wildfire Suppression

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89 items • Updated about 8 hours ago

Evaluation results

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

0.015272001700941474 +/- 0.008560343748877621
Extinguishing Trees on hivex-aerial-wildfire-suppression
self-reported

0.16764693087898194 +/- 0.19795760638271612
Extinguishing Trees Reward on hivex-aerial-wildfire-suppression
self-reported

0.8382346628699452 +/- 0.9897880220029962
Preparing Trees on hivex-aerial-wildfire-suppression
self-reported

295.1830795288086 +/- 11.336644749563497
Preparing Trees Reward on hivex-aerial-wildfire-suppression
self-reported

295.1830795288086 +/- 11.336644749563497
Water Drop on hivex-aerial-wildfire-suppression
self-reported

0.9843656837940216 +/- 0.008887930230304724
Water Pickup on hivex-aerial-wildfire-suppression
self-reported

0.0007015933631919324 +/- 0.001493842309054032
Cumulative Reward on hivex-aerial-wildfire-suppression
self-reported

294.59887542724607 +/- 11.330578758684899

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