--- library_name: hivex original_train_name: AerialWildfireSuppression_difficulty_6_task_1_run_id_1_train tags: - hivex - hivex-aerial-wildfire-suppression - reinforcement-learning - multi-agent-reinforcement-learning model-index: - name: hivex-AWS-PPO-baseline-task-1-difficulty-6 results: - task: type: sub-task name: maximize_extinguished_burning_trees task-id: 1 difficulty-id: 6 dataset: name: hivex-aerial-wildfire-suppression type: hivex-aerial-wildfire-suppression metrics: - type: crash_count value: 0.15000000447034836 +/- 0.20160177895130083 name: Crash Count verified: true - type: extinguishing_trees value: 21.208333425223827 +/- 28.328527795039527 name: Extinguishing Trees verified: true - type: extinguishing_trees_reward value: 1060.4166695594788 +/- 1416.426402849315 name: Extinguishing Trees Reward verified: true - type: fire_out value: 0.17500000223517417 +/- 0.2885484972637629 name: Fire Out verified: true - type: fire_too_close_to_city value: 0.9 +/- 0.26157418189029846 name: Fire too Close to City verified: true - type: preparing_trees value: 620.0166644275189 +/- 644.0197330961348 name: Preparing Trees verified: true - type: preparing_trees_reward value: 620.0166644275189 +/- 644.0197330961348 name: Preparing Trees Reward verified: true - type: water_drop value: 48.40833265781403 +/- 37.70947155566527 name: Water Drop verified: true - type: water_pickup value: 48.12500007152558 +/- 37.613333288243446 name: Water Pickup verified: true - type: cumulative_reward value: 1735.4933523178101 +/- 1718.2560586121042 name: Cumulative Reward verified: true --- 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](https://github.com/hivex-research/hivex)
Download the [Environment](https://github.com/hivex-research/hivex-environments)