metadata
library_name: hivex
original_train_name: DroneBasedReforestation_difficulty_2_task_5_run_id_2_train
tags:
- hivex
- hivex-drone-based-reforestation
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-DBR-PPO-baseline-task-5-difficulty-2
results:
- task:
type: sub-task
name: find_highest_potential_seed_drop_location
task-id: 5
difficulty-id: 2
dataset:
name: hivex-drone-based-reforestation
type: hivex-drone-based-reforestation
metrics:
- type: highest_point_on_terrain_found
value: 46.00852752685547 +/- 4.236103833992731
name: Highest Point on Terrain Found
verified: true
- type: out_of_energy_count
value: 0.6642222416400909 +/- 0.0670919881726494
name: Out of Energy Count
verified: true
- type: cumulative_reward
value: 45.137940902709964 +/- 3.701789346239036
name: Cumulative Reward
verified: true
This model serves as the baseline for the Drone-Based Reforestation environment, trained and tested on task 5 with difficulty 2 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Drone-Based Reforestation
Task: 5
Difficulty: 2
Algorithm: PPO
Episode Length: 2000
Training max_steps: 1200000
Testing max_steps: 300000
Train & Test Scripts
Download the Environment