---
library_name: hivex
original_train_name: DroneBasedReforestation_difficulty_6_task_0_run_id_2_train
tags:
- hivex
- hivex-drone-based-reforestation
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-DBR-PPO-baseline-task-0-difficulty-6
  results:
  - task:
      type: main-task
      name: main_task
      task-id: 0
      difficulty-id: 6
    dataset:
      name: hivex-drone-based-reforestation
      type: hivex-drone-based-reforestation
    metrics:
    - type: cumulative_distance_reward
      value: 2.278297426700592 +/- 0.7970550172943512
      name: Cumulative Distance Reward
      verified: true
    - type: cumulative_distance_until_tree_drop
      value: 71.83662818908691 +/- 16.138112577766993
      name: Cumulative Distance Until Tree Drop
      verified: true
    - type: cumulative_distance_to_existing_trees
      value: 63.50090087890625 +/- 12.724329294351138
      name: Cumulative Distance to Existing Trees
      verified: true
    - type: cumulative_normalized_distance_until_tree_drop
      value: 0.22782974272966386 +/- 0.07970550120723825
      name: Cumulative Normalized Distance Until Tree Drop
      verified: true
    - type: cumulative_tree_drop_reward
      value: 6.105163459777832 +/- 2.096869181395617
      name: Cumulative Tree Drop Reward
      verified: true
    - type: out_of_energy_count
      value: 0.9176825439929962 +/- 0.07301305856737815
      name: Out of Energy Count
      verified: true
    - type: recharge_energy_count
      value: 10.315396842956543 +/- 1.078328692209581
      name: Recharge Energy Count
      verified: true
    - type: tree_drop_count
      value: 1.0677143037319183 +/- 0.07302193295701627
      name: Tree Drop Count
      verified: true
    - type: cumulative_reward
      value: 9.875887503623963 +/- 3.754279000733476
      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>6</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Drone-Based Reforestation**<br>Task: <code>0</code><br>Difficulty: <code>6</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)