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--- |
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library_name: hivex |
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original_train_name: WildfireResourceManagement_difficulty_9_task_1_run_id_2_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-9 |
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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: 9 |
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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: 256.54253845214845 +/- 82.7350530070222 |
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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: 43.02604579925537 +/- 13.287361543787155 |
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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: 23.407614994049073 +/- 7.450801825115115 |
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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: 1.6655276775360108 +/- 0.5314602326491544 |
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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: 197.1991439819336 +/- 65.86970427316282 |
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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>9</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>9</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) |
