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---

library_name: hivex
original_train_name: DroneBasedReforestation_difficulty_4_task_0_run_id_1_train
tags:
- hivex
- hivex-drone-based-reforestation
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-DBR-PPO-baseline-task-0-difficulty-4
  results:
  - task:
      type: main-task
      name: main_task
      task-id: 0
      difficulty-id: 4
    dataset:
      name: hivex-drone-based-reforestation
      type: hivex-drone-based-reforestation
    metrics:
    - type: cumulative_distance_reward
      value: 2.2025150191783904 +/- 0.8048838225723474
      name: Cumulative Distance Reward
      verified: true
    - type: cumulative_distance_until_tree_drop
      value: 70.3463491821289 +/- 13.872446958274292
      name: Cumulative Distance Until Tree Drop
      verified: true
    - type: cumulative_distance_to_existing_trees
      value: 63.00524223327637 +/- 14.558269040918253
      name: Cumulative Distance to Existing Trees
      verified: true
    - type: cumulative_normalized_distance_until_tree_drop
      value: 0.2202515023946762 +/- 0.08048838503417874
      name: Cumulative Normalized Distance Until Tree Drop
      verified: true
    - type: cumulative_tree_drop_reward
      value: 5.9483204627037045 +/- 2.3428193553001173
      name: Cumulative Tree Drop Reward
      verified: true
    - type: out_of_energy_count
      value: 0.9133015894889831 +/- 0.07074894155629612
      name: Out of Energy Count
      verified: true
    - type: recharge_energy_count
      value: 11.649015922546386 +/- 1.7220237341546332
      name: Recharge Energy Count
      verified: true
    - type: tree_drop_count
      value: 1.0417143070697785 +/- 0.08413648907043028
      name: Tree Drop Count
      verified: true
    - type: cumulative_reward
      value: 9.298489372730256 +/- 3.9538719454855293
      name: Cumulative Reward
      verified: true
---


This model serves as the baseline for the **Drone-Based Reforestation** environment, trained and tested on task <code>0</code> with difficulty <code>4</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Drone-Based Reforestation**<br>Task: <code>0</code><br>Difficulty: <code>4</code><br>Algorithm: <code>PPO</code><br>Episode Length: <code>2000</code><br>Training <code>max_steps</code>: <code>1200000</code><br>Testing <code>max_steps</code>: <code>300000</code><br><br>Train & Test [Scripts](https://github.com/hivex-research/hivex)<br>Download the [Environment](https://github.com/hivex-research/hivex-environments)