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--- |
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library_name: hivex |
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original_train_name: AerialWildfireSuppression_difficulty_3_task_5_run_id_1_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-5-difficulty-3 |
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results: |
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- task: |
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type: sub-task |
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name: pick_up_water |
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task-id: 5 |
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difficulty-id: 3 |
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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: water_pickup |
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value: 0.9977272719144821 +/- 0.010163948987181867 |
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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: 94.67084541320801 +/- 0.6861259192735064 |
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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>5</code> with difficulty <code>3</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>5</code><br> |
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Difficulty: <code>3</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 |
