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---

library_name: hivex
original_train_name: AerialWildfireSuppression_difficulty_8_task_1_run_id_2_train
tags:
- hivex
- hivex-aerial-wildfire-suppression
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-AWS-PPO-baseline-task-1-difficulty-8
  results:
  - task:
      type: sub-task
      name: maximize_extinguished_burning_trees
      task-id: 1
      difficulty-id: 8
    dataset:
      name: hivex-aerial-wildfire-suppression
      type: hivex-aerial-wildfire-suppression
    metrics:
    - type: crash_count
      value: 0.30833334252238276 +/- 0.2771777226968141
      name: Crash Count
      verified: true
    - type: extinguishing_trees
      value: 28.216666746139527 +/- 38.8679015625057
      name: Extinguishing Trees
      verified: true
    - type: extinguishing_trees_reward
      value: 1410.833318901062 +/- 1943.3950349162335
      name: Extinguishing Trees Reward
      verified: true
    - type: fire_out
      value: 0.06666666865348816 +/- 0.16578715799245552
      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: 592.4916698455811 +/- 571.7471548283543
      name: Preparing Trees
      verified: true
    - type: preparing_trees_reward
      value: 592.4916698455811 +/- 571.7471548283543
      name: Preparing Trees Reward
      verified: true
    - type: water_drop
      value: 45.858332777023314 +/- 19.358443427747147
      name: Water Drop
      verified: true
    - type: water_pickup
      value: 45.541666460037234 +/- 19.38731633910842
      name: Water Pickup
      verified: true
    - type: cumulative_reward
      value: 1881.6991638183595 +/- 1414.2531270122881
      name: Cumulative Reward
      verified: true
---


This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task <code>1</code> with difficulty <code>8</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>

Environment: **Aerial Wildfire Suppression**<br>
Task: <code>1</code><br>
Difficulty: <code>8</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)