--- library_name: hivex original_train_name: AerialWildfireSuppression_difficulty_5_task_2_run_id_1_train tags: - hivex - hivex-aerial-wildfire-suppression - reinforcement-learning - multi-agent-reinforcement-learning model-index: - name: hivex-AWS-PPO-baseline-task-2-difficulty-5 results: - task: type: sub-task name: maximize_preparing_non_burning_trees task-id: 2 difficulty-id: 5 dataset: name: hivex-aerial-wildfire-suppression type: hivex-aerial-wildfire-suppression metrics: - type: crash_count value: 0.25000000521540644 +/- 0.26765169236445613 name: Crash Count verified: true - type: extinguishing_trees value: 26.541666515916585 +/- 71.99835260789617 name: Extinguishing Trees verified: true - type: extinguishing_trees_reward value: 132.70833393633364 +/- 359.9917639236706 name: Extinguishing Trees Reward verified: true - type: fire_out value: 0.1916666693985462 +/- 0.3301381975702533 name: Fire Out verified: true - type: fire_too_close_to_city value: 0.975 +/- 0.11180339887498947 name: Fire too Close to City verified: true - type: preparing_trees value: 884.999996471405 +/- 751.8528699660257 name: Preparing Trees verified: true - type: preparing_trees_reward value: 4425.0000263214115 +/- 3759.264413506219 name: Preparing Trees Reward verified: true - type: water_drop value: 53.89166679382324 +/- 27.40039192850323 name: Water Drop verified: true - type: water_pickup value: 53.56666660308838 +/- 27.298244112627053 name: Water Pickup verified: true - type: cumulative_reward value: 5174.121683979034 +/- 4124.406680944283 name: Cumulative Reward verified: true --- This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task 2 with difficulty 5 using the Proximal Policy Optimization (PPO) algorithm.

Environment: **Aerial Wildfire Suppression**
Task: 2
Difficulty: 5
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)