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---

library_name: hivex
original_train_name: DroneBasedReforestation_difficulty_2_task_3_run_id_2_train
tags:
- hivex
- hivex-drone-based-reforestation
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-DBR-PPO-baseline-task-3-difficulty-2
  results:
  - task:
      type: sub-task
      name: drop_seed
      task-id: 3
      difficulty-id: 2
    dataset:
      name: hivex-drone-based-reforestation
      type: hivex-drone-based-reforestation
    metrics:
    - type: cumulative_distance_reward
      value: 1.2730848133563994 +/- 0.31384063871152373
      name: Cumulative Distance Reward
      verified: true
    - type: cumulative_distance_until_tree_drop
      value: 46.571126289367676 +/- 6.711804112230181
      name: Cumulative Distance Until Tree Drop
      verified: true
    - type: cumulative_distance_to_existing_trees
      value: 62.378562469482425 +/- 4.8385232941913126
      name: Cumulative Distance to Existing Trees
      verified: true
    - type: cumulative_normalized_distance_until_tree_drop
      value: 0.12730848103761672 +/- 0.03138406355454151
      name: Cumulative Normalized Distance Until Tree Drop
      verified: true
    - type: cumulative_tree_drop_reward
      value: 4.010982251167297 +/- 0.6601700266326962
      name: Cumulative Tree Drop Reward
      verified: true
    - type: out_of_energy_count
      value: 0.05754003098234534 +/- 0.03282736545941193
      name: Out of Energy Count
      verified: true
    - type: recharge_energy_count
      value: 11.035588264465332 +/- 0.725159645414964
      name: Recharge Energy Count
      verified: true
    - type: tree_drop_count
      value: 0.9222618734836578 +/- 0.04192513553044461
      name: Tree Drop Count
      verified: true
    - type: cumulative_reward
      value: 98.53370529174805 +/- 5.198916602319761
      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>2</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Drone-Based Reforestation**<br>Task: <code>3</code><br>Difficulty: <code>2</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)