---
library_name: hivex
original_train_name: AerialWildfireSuppression_difficulty_10_task_2_run_id_1_train
tags:
- hivex
- hivex-aerial-wildfire-suppression
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-AWS-PPO-baseline-task-2-difficulty-10
  results:
  - task:
      type: sub-task
      name: maximize_preparing_non_burning_trees
      task-id: 2
      difficulty-id: 10
    dataset:
      name: hivex-aerial-wildfire-suppression
      type: hivex-aerial-wildfire-suppression
    metrics:
    - type: crash_count
      value: 0.15833333730697632 +/- 0.20572934499076767
      name: Crash Count
      verified: true
    - type: extinguishing_trees
      value: 19.241666620969774 +/- 33.273080342427235
      name: Extinguishing Trees
      verified: true
    - type: extinguishing_trees_reward
      value: 96.20833342075348 +/- 166.36540223877446
      name: Extinguishing Trees Reward
      verified: true
    - type: fire_out
      value: 0.20833333507180213 +/- 0.32387908421054906
      name: Fire Out
      verified: true
    - type: fire_too_close_to_city
      value: 0.95 +/- 0.22360679774997894
      name: Fire too Close to City
      verified: true
    - type: preparing_trees
      value: 995.8083220481873 +/- 896.6925434987216
      name: Preparing Trees
      verified: true
    - type: preparing_trees_reward
      value: 4979.041623306274 +/- 4483.462788982591
      name: Preparing Trees Reward
      verified: true
    - type: water_drop
      value: 36.908333444595335 +/- 20.718840949931526
      name: Water Drop
      verified: true
    - type: water_pickup
      value: 36.41666669845581 +/- 20.746415247545407
      name: Water Pickup
      verified: true
    - type: cumulative_reward
      value: 5726.971720504761 +/- 3142.936334111313
      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>10</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>

Environment: **Aerial Wildfire Suppression**<br>
Task: <code>2</code><br>
Difficulty: <code>10</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)