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---
library_name: hivex
original_train_name: AerialWildfireSuppression_difficulty_7_task_4_run_id_0_train
tags:
- hivex
- hivex-aerial-wildfire-suppression
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-AWS-PPO-baseline-task-4-difficulty-7
results:
- task:
type: sub-task
name: protect_village
task-id: 4
difficulty-id: 7
dataset:
name: hivex-aerial-wildfire-suppression
type: hivex-aerial-wildfire-suppression
metrics:
- type: crash_count
value: 0.996428570151329 +/- 0.015971919837000092
name: Crash Count
verified: true
- type: extinguishing_trees
value: 0.5590403918176889 +/- 2.1770827274580227
name: Extinguishing Trees
verified: true
- type: extinguishing_trees_reward
value: 2.7952019572257996 +/- 10.88541363667466
name: Extinguishing Trees Reward
verified: true
- type: fire_too_close_to_city
value: 0.010128205269575119 +/- 0.031176732946782266
name: Fire too Close to City
verified: true
- type: preparing_trees
value: 289.3235092163086 +/- 35.916303930832015
name: Preparing Trees
verified: true
- type: preparing_trees_reward
value: 289.3235092163086 +/- 35.916303930832015
name: Preparing Trees Reward
verified: true
- type: water_drop
value: 1.8651554942131043 +/- 0.2548557205509962
name: Water Drop
verified: true
- type: water_pickup
value: 1.8651554942131043 +/- 0.2548557205509962
name: Water Pickup
verified: true
- type: cumulative_reward
value: 189.838374710083 +/- 30.620179554518494
name: Cumulative Reward
verified: true
---
This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task <code>4</code> with difficulty <code>7</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>
Environment: **Aerial Wildfire Suppression**<br>
Task: <code>4</code><br>
Difficulty: <code>7</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) |