---
library_name: hivex
original_train_name: AerialWildfireSuppression_difficulty_7_task_2_run_id_2_train
tags:
- hivex
- hivex-aerial-wildfire-suppression
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-AWS-PPO-baseline-task-2-difficulty-7
  results:
  - task:
      type: sub-task
      name: maximize_preparing_non_burning_trees
      task-id: 2
      difficulty-id: 7
    dataset:
      name: hivex-aerial-wildfire-suppression
      type: hivex-aerial-wildfire-suppression
    metrics:
    - type: crash_count
      value: 0.41666667610406877 +/- 0.29369595331135534
      name: Crash Count
      verified: true
    - type: extinguishing_trees
      value: 26.98611140549183 +/- 45.067904043919626
      name: Extinguishing Trees
      verified: true
    - type: extinguishing_trees_reward
      value: 134.9305568575859 +/- 225.33952073669184
      name: Extinguishing Trees Reward
      verified: true
    - type: fire_out
      value: 0.09166666939854622 +/- 0.1375963286810061
      name: Fire Out
      verified: true
    - type: fire_too_close_to_city
      value: 0.9833333343267441 +/- 0.07453559480732508
      name: Fire too Close to City
      verified: true
    - type: preparing_trees
      value: 915.0361038208008 +/- 630.722632747104
      name: Preparing Trees
      verified: true
    - type: preparing_trees_reward
      value: 4575.180584716797 +/- 3153.613200762862
      name: Preparing Trees Reward
      verified: true
    - type: water_drop
      value: 63.81111078262329 +/- 27.460713193319517
      name: Water Drop
      verified: true
    - type: water_pickup
      value: 63.5777774810791 +/- 27.43349377033259
      name: Water Pickup
      verified: true
    - type: cumulative_reward
      value: 4956.189190673828 +/- 2576.604065716017
      name: Cumulative Reward
      verified: true
---

This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task <code>2</code> with difficulty <code>7</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>

Environment: **Aerial Wildfire Suppression**<br>
Task: <code>2</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)