--- library_name: hivex original_train_name: AerialWildfireSuppression_difficulty_10_task_3_run_id_2_train tags: - hivex - hivex-aerial-wildfire-suppression - reinforcement-learning - multi-agent-reinforcement-learning model-index: - name: hivex-AWS-PPO-baseline-task-3-difficulty-10 results: - task: type: sub-task name: minimize_time_fire_burning task-id: 3 difficulty-id: 10 dataset: name: hivex-aerial-wildfire-suppression type: hivex-aerial-wildfire-suppression metrics: - type: crash_count value: 0.21666667088866234 +/- 0.25989201752505897 name: Crash Count verified: true - type: extinguishing_trees value: 23.541666555404664 +/- 25.76001879059616 name: Extinguishing Trees verified: true - type: extinguishing_trees_reward value: 117.70833463668824 +/- 128.80009751865373 name: Extinguishing Trees Reward verified: true - type: fire_out value: 0.25000000596046446 +/- 0.3176117073446609 name: Fire Out verified: true - type: fire_too_close_to_city value: 0.95 +/- 0.22360679774997894 name: Fire too Close to City verified: true - type: preparing_trees value: 842.3416595458984 +/- 719.565955429358 name: Preparing Trees verified: true - type: preparing_trees_reward value: 842.3416595458984 +/- 719.565955429358 name: Preparing Trees Reward verified: true - type: water_drop value: 56.20000038146973 +/- 35.51066867416029 name: Water Drop verified: true - type: water_pickup value: 55.85000023841858 +/- 35.4871245294335 name: Water Pickup verified: true - type: cumulative_reward value: 1050.1918411254883 +/- 490.0267879628168 name: Cumulative Reward verified: true --- This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task 3 with difficulty 10 using the Proximal Policy Optimization (PPO) algorithm.

Environment: **Aerial Wildfire Suppression**
Task: 3
Difficulty: 10
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)