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---
library_name: hivex
original_train_name: AerialWildfireSuppression_difficulty_9_task_0_run_id_1_train
tags:
- hivex
- hivex-aerial-wildfire-suppression
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-AWS-PPO-baseline-task-0-difficulty-9
results:
- task:
type: main-task
name: main_task
task-id: 0
difficulty-id: 9
dataset:
name: hivex-aerial-wildfire-suppression
type: hivex-aerial-wildfire-suppression
metrics:
- type: crash_count
value: 0.24166667386889457 +/- 0.1750104476777611
name: Crash Count
verified: true
- type: extinguishing_trees
value: 17.141666746139528 +/- 39.513165920891936
name: Extinguishing Trees
verified: true
- type: extinguishing_trees_reward
value: 85.70833311080932 +/- 197.56582920337453
name: Extinguishing Trees Reward
verified: true
- type: fire_out
value: 0.12500000223517418 +/- 0.24106852927463382
name: Fire Out
verified: true
- type: fire_too_close_to_city
value: 0.9 +/- 0.2615741818902984
name: Fire too Close to City
verified: true
- type: preparing_trees
value: 721.7666670084 +/- 737.4681856167363
name: Preparing Trees
verified: true
- type: preparing_trees_reward
value: 721.7666670084 +/- 737.4681856167363
name: Preparing Trees Reward
verified: true
- type: water_drop
value: 66.28333377838135 +/- 30.644495531353783
name: Water Drop
verified: true
- type: water_pickup
value: 65.93333344459533 +/- 30.521844562150648
name: Water Pickup
verified: true
- type: cumulative_reward
value: 996.1558359742164 +/- 875.8416918638716
name: Cumulative Reward
verified: true
---
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>
Environment: **Aerial Wildfire Suppression**<br>
Task: <code>0</code><br>
Difficulty: <code>9</code><br>
Algorithm: <code>PPO</code><br>
Episode Length: <code>3000</code><br>
Training <code>max_steps</code>: <code>1800000</code><br>
Testing <code>max_steps</code>: <code>180000</code><br><br>
Train & Test [Scripts](https://github.com/hivex-research/hivex)<br>
Download the [Environment](https://github.com/hivex-research/hivex-environments) |