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---
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library_name: hivex
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original_train_name: AerialWildfireSuppression_difficulty_8_task_0_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-0-difficulty-8
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results:
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- task:
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type: main-task
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name: main_task
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task-id: 0
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difficulty-id: 8
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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: 0.10833333656191826 +/- 0.14584900099920892
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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: 23.324999898672104 +/- 55.08031019150775
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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: 116.62500007152558 +/- 275.40155086604756
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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: 0.22500000149011612 +/- 0.3638448035924671
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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: 0.85 +/- 0.28562028528873973
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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: 769.4333295822144 +/- 713.797537109146
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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: 769.4333295822144 +/- 713.797537109146
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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: 42.46666691303253 +/- 16.681099284118027
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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: 42.0666668176651 +/- 16.62014604652166
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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: 1093.1966667175293 +/- 733.5777441210589
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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>0</code> with difficulty <code>8</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>0</code><br>
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Difficulty: <code>8</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) |
