--- library_name: hivex original_train_name: AerialWildfireSuppression_difficulty_10_task_4_run_id_0_train tags: - hivex - hivex-aerial-wildfire-suppression - reinforcement-learning - multi-agent-reinforcement-learning model-index: - name: hivex-AWS-PPO-baseline-task-4-difficulty-10 results: - task: type: sub-task name: protect_village task-id: 4 difficulty-id: 10 dataset: name: hivex-aerial-wildfire-suppression type: hivex-aerial-wildfire-suppression metrics: - type: crash_count value: 0.9949999988079071 +/- 0.022360685106199443 name: Crash Count verified: true - type: extinguishing_trees value: 0.29754857206717134 +/- 0.6612722591280618 name: Extinguishing Trees verified: true - type: extinguishing_trees_reward value: 1.4877428144216538 +/- 3.3063611877410133 name: Extinguishing Trees Reward verified: true - type: fire_too_close_to_city value: 0.022103730216622354 +/- 0.039482863821780616 name: Fire too Close to City verified: true - type: preparing_trees value: 274.65237579345705 +/- 34.49504850001327 name: Preparing Trees verified: true - type: preparing_trees_reward value: 274.65237579345705 +/- 34.49504850001327 name: Preparing Trees Reward verified: true - type: water_drop value: 2.101252889633179 +/- 0.3808157213259622 name: Water Drop verified: true - type: water_pickup value: 2.101252889633179 +/- 0.3808157213259622 name: Water Pickup verified: true - type: cumulative_reward value: 168.44546432495116 +/- 38.14918935961842 name: Cumulative Reward verified: true --- This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task 4 with difficulty 10 using the Proximal Policy Optimization (PPO) algorithm.

Environment: **Aerial Wildfire Suppression**
Task: 4
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)