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---

library_name: hivex
original_train_name: AerialWildfireSuppression_difficulty_5_task_6_run_id_2_train
tags:
- hivex
- hivex-aerial-wildfire-suppression
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-AWS-PPO-baseline-task-6-difficulty-5
  results:
  - task:
      type: sub-task
      name: drop_water
      task-id: 6
      difficulty-id: 5
    dataset:
      name: hivex-aerial-wildfire-suppression
      type: hivex-aerial-wildfire-suppression
    metrics:
    - type: crash_count
      value: 0.022751575300935654 +/- 0.009602885208751202
      name: Crash Count
      verified: true
    - type: extinguishing_trees
      value: 0.2077373639680445 +/- 0.1507774190085061
      name: Extinguishing Trees
      verified: true
    - type: extinguishing_trees_reward
      value: 1.0386868014931678 +/- 0.753887068245034
      name: Extinguishing Trees Reward
      verified: true
    - type: preparing_trees
      value: 275.6179458618164 +/- 12.486733727275665
      name: Preparing Trees
      verified: true
    - type: preparing_trees_reward
      value: 275.6179458618164 +/- 12.486733727275665
      name: Preparing Trees Reward
      verified: true
    - type: water_drop
      value: 0.9767484277486801 +/- 0.00989079886411895
      name: Water Drop
      verified: true
    - type: water_pickup
      value: 0.0005922459880821407 +/- 0.0015700193469281448
      name: Water Pickup
      verified: true
    - type: cumulative_reward
      value: 274.48731155395507 +/- 13.254462171454286
      name: Cumulative Reward
      verified: true
---


This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task <code>6</code> with difficulty <code>5</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>

Environment: **Aerial Wildfire Suppression**<br>
Task: <code>6</code><br>
Difficulty: <code>5</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)