---
library_name: hivex
original_train_name: AerialWildfireSuppression_difficulty_3_task_2_run_id_0_train
tags:
- hivex
- hivex-aerial-wildfire-suppression
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-AWS-PPO-baseline-task-2-difficulty-3
  results:
  - task:
      type: sub-task
      name: maximize_preparing_non_burning_trees
      task-id: 2
      difficulty-id: 3
    dataset:
      name: hivex-aerial-wildfire-suppression
      type: hivex-aerial-wildfire-suppression
    metrics:
    - type: crash_count
      value: 0.0833333358168602 +/- 0.1378617027533506
      name: Crash Count
      verified: true
    - type: extinguishing_trees
      value: 18.683333218097687 +/- 27.558120115325824
      name: Extinguishing Trees
      verified: true
    - type: extinguishing_trees_reward
      value: 93.41666712760926 +/- 137.79060314424476
      name: Extinguishing Trees Reward
      verified: true
    - type: fire_out
      value: 0.35833333656191824 +/- 0.36784102365159543
      name: Fire Out
      verified: true
    - type: fire_too_close_to_city
      value: 0.975 +/- 0.11180339887498947
      name: Fire too Close to City
      verified: true
    - type: preparing_trees
      value: 556.9166661500931 +/- 491.4252421024537
      name: Preparing Trees
      verified: true
    - type: preparing_trees_reward
      value: 2784.5833506584167 +/- 2457.1262108957085
      name: Preparing Trees Reward
      verified: true
    - type: water_drop
      value: 39.591666674613954 +/- 20.687346400193867
      name: Water Drop
      verified: true
    - type: water_pickup
      value: 39.18333334922791 +/- 20.631967029054877
      name: Water Pickup
      verified: true
    - type: cumulative_reward
      value: 2911.9833114624025 +/- 2372.473518108635
      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>3</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>

Environment: **Aerial Wildfire Suppression**<br>
Task: <code>2</code><br>
Difficulty: <code>3</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)