---
library_name: hivex
original_train_name: DroneBasedReforestation_difficulty_10_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-10
  results:
  - task:
      type: sub-task
      name: drop_seed
      task-id: 3
      difficulty-id: 10
    dataset:
      name: hivex-drone-based-reforestation
      type: hivex-drone-based-reforestation
    metrics:
    - type: cumulative_distance_reward
      value: 1.3822244083881379 +/- 0.2799904225640544
      name: Cumulative Distance Reward
      verified: true
    - type: cumulative_distance_until_tree_drop
      value: 49.66127479553223 +/- 7.218445332813338
      name: Cumulative Distance Until Tree Drop
      verified: true
    - type: cumulative_distance_to_existing_trees
      value: 65.08539611816406 +/- 5.7159717268853285
      name: Cumulative Distance to Existing Trees
      verified: true
    - type: cumulative_normalized_distance_until_tree_drop
      value: 0.13822243928909303 +/- 0.027999042034590665
      name: Cumulative Normalized Distance Until Tree Drop
      verified: true
    - type: cumulative_tree_drop_reward
      value: 4.014332270622253 +/- 0.740893757159681
      name: Cumulative Tree Drop Reward
      verified: true
    - type: out_of_energy_count
      value: 0.03652440816164017 +/- 0.02224060499692208
      name: Out of Energy Count
      verified: true
    - type: recharge_energy_count
      value: 10.598072090148925 +/- 0.5897619835270185
      name: Recharge Energy Count
      verified: true
    - type: tree_drop_count
      value: 0.9516399455070496 +/- 0.03216850980609787
      name: Tree Drop Count
      verified: true
    - type: cumulative_reward
      value: 101.69934463500977 +/- 3.379470856148503
      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>10</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Drone-Based Reforestation**<br>Task: <code>3</code><br>Difficulty: <code>10</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)