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---

library_name: hivex
original_train_name: DroneBasedReforestation_difficulty_1_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-1
  results:
  - task:
      type: main-task
      name: main_task
      task-id: 0
      difficulty-id: 1
    dataset:
      name: hivex-drone-based-reforestation
      type: hivex-drone-based-reforestation
    metrics:
    - type: cumulative_distance_reward
      value: 2.0864201402664184 +/- 0.6296944874797746
      name: Cumulative Distance Reward
      verified: true
    - type: cumulative_distance_until_tree_drop
      value: 63.19091514587402 +/- 12.303839558575664
      name: Cumulative Distance Until Tree Drop
      verified: true
    - type: cumulative_distance_to_existing_trees
      value: 61.76650863647461 +/- 13.908253887773586
      name: Cumulative Distance to Existing Trees
      verified: true
    - type: cumulative_normalized_distance_until_tree_drop
      value: 0.20864201247692107 +/- 0.06296944883377423
      name: Cumulative Normalized Distance Until Tree Drop
      verified: true
    - type: cumulative_tree_drop_reward
      value: 5.931592869758606 +/- 1.8518746378631161
      name: Cumulative Tree Drop Reward
      verified: true
    - type: out_of_energy_count
      value: 0.9266984140872956 +/- 0.06184757754397895
      name: Out of Energy Count
      verified: true
    - type: recharge_energy_count
      value: 10.601777839660645 +/- 1.2478378815502142
      name: Recharge Energy Count
      verified: true
    - type: tree_drop_count
      value: 1.0418095350265504 +/- 0.08056789785926544
      name: Tree Drop Count
      verified: true
    - type: cumulative_reward
      value: 8.961133165359497 +/- 2.7381643935331064
      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>1</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Drone-Based Reforestation**<br>Task: <code>0</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)