---
library_name: hivex
original_train_name: DroneBasedReforestation_difficulty_8_task_0_run_id_1_train
tags:
- hivex
- hivex-drone-based-reforestation
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-DBR-PPO-baseline-task-0-difficulty-8
results:
- task:
type: main-task
name: main_task
task-id: 0
difficulty-id: 8
dataset:
name: hivex-drone-based-reforestation
type: hivex-drone-based-reforestation
metrics:
- type: cumulative_distance_reward
value: 2.231035829782486 +/- 0.8328265468613688
name: Cumulative Distance Reward
verified: true
- type: cumulative_distance_until_tree_drop
value: 66.65770332336426 +/- 16.760894397204105
name: Cumulative Distance Until Tree Drop
verified: true
- type: cumulative_distance_to_existing_trees
value: 61.44380241394043 +/- 13.630261327963224
name: Cumulative Distance to Existing Trees
verified: true
- type: cumulative_normalized_distance_until_tree_drop
value: 0.22310358494520188 +/- 0.08328265504237621
name: Cumulative Normalized Distance Until Tree Drop
verified: true
- type: cumulative_tree_drop_reward
value: 5.744872629642487 +/- 1.9187415652465019
name: Cumulative Tree Drop Reward
verified: true
- type: out_of_energy_count
value: 0.9406349241733551 +/- 0.06549559550080679
name: Out of Energy Count
verified: true
- type: recharge_energy_count
value: 10.602158679962159 +/- 1.2842570609336479
name: Recharge Energy Count
verified: true
- type: tree_drop_count
value: 1.0329841363430023 +/- 0.06435620343022462
name: Tree Drop Count
verified: true
- type: cumulative_reward
value: 8.81026906967163 +/- 3.1991946865922416
name: Cumulative Reward
verified: true
---
This model serves as the baseline for the **Drone-Based Reforestation** environment, trained and tested on task 0
with difficulty 8
using the Proximal Policy Optimization (PPO) algorithm.
Environment: **Drone-Based Reforestation**
Task: 0
Difficulty: 8
Algorithm: PPO
Episode Length: 2000
Training max_steps
: 1200000
Testing max_steps
: 300000
Train & Test [Scripts](https://github.com/hivex-research/hivex)
Download the [Environment](https://github.com/hivex-research/hivex-environments)