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---
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library_name: hivex
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original_train_name: AerialWildfireSuppression_difficulty_9_task_2_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-2-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_preparing_non_burning_trees
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task-id: 2
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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: 0.09166666939854622 +/- 0.18317377972526547
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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: 8.949999886751176 +/- 12.562137901097202
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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: 44.75000040531158 +/- 62.81068995864626
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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: 0.3500000022351742 +/- 0.4114586818171751
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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: 0.975 +/- 0.11180339887498947
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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: 652.12500230968 +/- 512.4888000138135
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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: 3260.6250272393227 +/- 2562.444032266141
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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: 65.37499959468842 +/- 34.89231000298373
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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: 64.99166650772095 +/- 34.92349427276053
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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: 3682.374974441528 +/- 2239.4285326262125
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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>2</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>2</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) |
