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---
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library_name: hivex
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original_train_name: AerialWildfireSuppression_difficulty_5_task_1_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-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: maximize_extinguished_burning_trees
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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-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: 0.15833333656191825 +/- 0.19098850564751765
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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: 20.000000047683717 +/- 35.87091048765571
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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: 999.9999992370606 +/- 1793.545528264617
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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: 0.10000000298023223 +/- 0.244231706300354
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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: 0.925 +/- 0.24468024246479642
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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: 439.2000018119812 +/- 486.4487458526075
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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: 439.2000018119812 +/- 486.4487458526075
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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: 35.9416666328907 +/- 21.80430457793747
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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: 35.77500002980232 +/- 21.714001930720748
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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: 1192.8983428001404 +/- 1401.6480393641084
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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>1</code> with difficulty <code>5</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>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>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) |
