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---
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library_name: hivex
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original_train_name: AerialWildfireSuppression_difficulty_9_task_0_run_id_1_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-9
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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: 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: 0.24166667386889457 +/- 0.1750104476777611
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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: 17.141666746139528 +/- 39.513165920891936
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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: 85.70833311080932 +/- 197.56582920337453
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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: 0.12500000223517418 +/- 0.24106852927463382
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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: 0.9 +/- 0.2615741818902984
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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: 721.7666670084 +/- 737.4681856167363
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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: 721.7666670084 +/- 737.4681856167363
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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: 66.28333377838135 +/- 30.644495531353783
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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: 65.93333344459533 +/- 30.521844562150648
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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: 996.1558359742164 +/- 875.8416918638716
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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>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>0</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) |
