---
library_name: hivex
original_train_name: DroneBasedReforestation_difficulty_9_task_3_run_id_1_train
tags:
- hivex
- hivex-drone-based-reforestation
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-DBR-PPO-baseline-task-3-difficulty-9
  results:
  - task:
      type: sub-task
      name: drop_seed
      task-id: 3
      difficulty-id: 9
    dataset:
      name: hivex-drone-based-reforestation
      type: hivex-drone-based-reforestation
    metrics:
    - type: cumulative_distance_reward
      value: 1.3542225050926209 +/- 0.23333899783579354
      name: Cumulative Distance Reward
      verified: true
    - type: cumulative_distance_until_tree_drop
      value: 49.953554458618164 +/- 6.4635271249103035
      name: Cumulative Distance Until Tree Drop
      verified: true
    - type: cumulative_distance_to_existing_trees
      value: 65.1268350982666 +/- 6.275221217555885
      name: Cumulative Distance to Existing Trees
      verified: true
    - type: cumulative_normalized_distance_until_tree_drop
      value: 0.13542225003242492 +/- 0.02333390047639469
      name: Cumulative Normalized Distance Until Tree Drop
      verified: true
    - type: cumulative_tree_drop_reward
      value: 4.086031370162964 +/- 0.8049852876065032
      name: Cumulative Tree Drop Reward
      verified: true
    - type: out_of_energy_count
      value: 0.03118088087067008 +/- 0.020989988346072946
      name: Out of Energy Count
      verified: true
    - type: recharge_energy_count
      value: 11.123015098571777 +/- 0.6124465630966653
      name: Recharge Energy Count
      verified: true
    - type: tree_drop_count
      value: 0.9591382348537445 +/- 0.028923095592019384
      name: Tree Drop Count
      verified: true
    - type: cumulative_reward
      value: 102.52203262329101 +/- 3.3865961577425283
      name: Cumulative Reward
      verified: true
---

This model serves as the baseline for the **Drone-Based Reforestation** environment, trained and tested on task <code>3</code> with difficulty <code>9</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Drone-Based Reforestation**<br>Task: <code>3</code><br>Difficulty: <code>9</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)