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--- |
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library_name: hivex |
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original_train_name: AerialWildfireSuppression_difficulty_9_task_1_run_id_2_train |
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tags: |
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- hivex |
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- hivex-aerial-wildfire-suppression |
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- reinforcement-learning |
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- multi-agent-reinforcement-learning |
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model-index: |
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- name: hivex-AWS-PPO-baseline-task-1-difficulty-9 |
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results: |
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- task: |
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type: sub-task |
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name: maximize_extinguished_burning_trees |
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task-id: 1 |
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difficulty-id: 9 |
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dataset: |
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name: hivex-aerial-wildfire-suppression |
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type: hivex-aerial-wildfire-suppression |
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metrics: |
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- type: crash_count |
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value: 0.38333334103226663 +/- 0.2709092371191193 |
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name: Crash Count |
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verified: true |
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- type: extinguishing_trees |
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value: 17.783333230018616 +/- 23.626856569133906 |
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name: Extinguishing Trees |
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verified: true |
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- type: extinguishing_trees_reward |
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value: 889.1666702270508 +/- 1181.3428509988885 |
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name: Extinguishing Trees Reward |
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verified: true |
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- type: fire_out |
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value: 0.10000000298023223 +/- 0.13679711768822556 |
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name: Fire Out |
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verified: true |
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- type: fire_too_close_to_city |
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value: 0.925 +/- 0.24468024246479642 |
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name: Fire too Close to City |
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verified: true |
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- type: preparing_trees |
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value: 669.3166633605957 +/- 541.9104371075354 |
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name: Preparing Trees |
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verified: true |
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- type: preparing_trees_reward |
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value: 669.3166633605957 +/- 541.9104371075354 |
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name: Preparing Trees Reward |
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verified: true |
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- type: water_drop |
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value: 25.191666746139525 +/- 15.035657045429138 |
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name: Water Drop |
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verified: true |
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- type: water_pickup |
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value: 25.01666667461395 +/- 15.04835278769134 |
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name: Water Pickup |
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verified: true |
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- type: cumulative_reward |
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value: 1912.962504005432 +/- 2485.098888848231 |
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name: Cumulative Reward |
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verified: true |
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--- |
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This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task <code>1</code> with difficulty <code>9</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br> |
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Environment: **Aerial Wildfire Suppression**<br> |
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Task: <code>1</code><br> |
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Difficulty: <code>9</code><br> |
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Algorithm: <code>PPO</code><br> |
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Episode Length: <code>3000</code><br> |
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Training <code>max_steps</code>: <code>1800000</code><br> |
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Testing <code>max_steps</code>: <code>180000</code><br><br> |
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Train & Test [Scripts](https://github.com/hivex-research/hivex)<br> |
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Download the [Environment](https://github.com/hivex-research/hivex-environments) |
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[hivex-paper]: https://arxiv.org/abs/2501.04180 |
