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--- |
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library_name: hivex |
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original_train_name: WildfireResourceManagement_difficulty_5_task_1_run_id_1_train |
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tags: |
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- hivex |
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- hivex-wildfire-resource-management |
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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-WRM-PPO-baseline-task-1-difficulty-5 |
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results: |
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- task: |
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type: sub-task |
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name: keep_all |
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task-id: 1 |
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difficulty-id: 5 |
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dataset: |
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name: hivex-wildfire-resource-management |
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type: hivex-wildfire-resource-management |
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metrics: |
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- type: cumulative_reward |
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value: 301.4590789794922 +/- 50.589352153281204 |
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name: "Cumulative Reward" |
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verified: true |
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- type: collective_performance |
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value: 52.42880744934082 +/- 13.213045945399395 |
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name: "Collective Performance" |
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verified: true |
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- type: individual_performance |
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value: 27.22167682647705 +/- 6.5057905262466 |
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name: "Individual Performance" |
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verified: true |
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- type: reward_for_moving_resources_to_neighbours |
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value: 1.2814587712287904 +/- 0.3169255575214482 |
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name: "Reward for Moving Resources to Neighbours" |
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verified: true |
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- type: reward_for_moving_resources_to_self |
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value: 233.32887573242186 +/- 58.13535329798181 |
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name: "Reward for Moving Resources to Self" |
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verified: true |
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--- |
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This model serves as the baseline for the **Wildfire Resource Management** environment, trained and tested on task <code>1</code> with difficulty <code>5</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br> |
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Environment: **Wildfire Resource Management**<br> |
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Task: <code>1</code><br> |
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Difficulty: <code>5</code><br> |
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Algorithm: <code>PPO</code><br> |
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Episode Length: <code>500</code><br> |
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Training <code>max_steps</code>: <code>450000</code><br> |
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Testing <code>max_steps</code>: <code>45000</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) |
