---
library_name: hivex
original_train_name: DroneBasedReforestation_difficulty_1_task_3_run_id_0_train
tags:
- hivex
- hivex-drone-based-reforestation
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-DBR-PPO-baseline-task-3-difficulty-1
  results:
  - task:
      type: sub-task
      name: drop_seed
      task-id: 3
      difficulty-id: 1
    dataset:
      name: hivex-drone-based-reforestation
      type: hivex-drone-based-reforestation
    metrics:
    - type: cumulative_distance_reward
      value: 1.1704939258098603 +/- 0.19094953820226412
      name: Cumulative Distance Reward
      verified: true
    - type: cumulative_distance_until_tree_drop
      value: 45.521212310791014 +/- 5.629736102757813
      name: Cumulative Distance Until Tree Drop
      verified: true
    - type: cumulative_distance_to_existing_trees
      value: 63.47206115722656 +/- 6.1461301353938405
      name: Cumulative Distance to Existing Trees
      verified: true
    - type: cumulative_normalized_distance_until_tree_drop
      value: 0.11704939216375351 +/- 0.019094953655432356
      name: Cumulative Normalized Distance Until Tree Drop
      verified: true
    - type: cumulative_tree_drop_reward
      value: 3.866243634223938 +/- 0.8022492017418626
      name: Cumulative Tree Drop Reward
      verified: true
    - type: out_of_energy_count
      value: 0.0493655932508409 +/- 0.028394293838768382
      name: Out of Energy Count
      verified: true
    - type: recharge_energy_count
      value: 10.92464771270752 +/- 0.6682069442874347
      name: Recharge Energy Count
      verified: true
    - type: tree_drop_count
      value: 0.9307654321193695 +/- 0.038764458231368655
      name: Tree Drop Count
      verified: true
    - type: cumulative_reward
      value: 99.16041168212891 +/- 4.422805341579576
      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>1</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Drone-Based Reforestation**<br>Task: <code>3</code><br>Difficulty: <code>1</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)