|
---
|
|
library_name: hivex
|
|
original_train_name: DroneBasedReforestation_difficulty_5_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-5
|
|
results:
|
|
- task:
|
|
type: sub-task
|
|
name: drop_seed
|
|
task-id: 3
|
|
difficulty-id: 5
|
|
dataset:
|
|
name: hivex-drone-based-reforestation
|
|
type: hivex-drone-based-reforestation
|
|
metrics:
|
|
- type: cumulative_distance_reward
|
|
value: 1.317925215959549 +/- 0.28260177110908363
|
|
name: Cumulative Distance Reward
|
|
verified: true
|
|
- type: cumulative_distance_until_tree_drop
|
|
value: 48.28620391845703 +/- 7.283860263327832
|
|
name: Cumulative Distance Until Tree Drop
|
|
verified: true
|
|
- type: cumulative_distance_to_existing_trees
|
|
value: 64.57429847717285 +/- 5.444324231140867
|
|
name: Cumulative Distance to Existing Trees
|
|
verified: true
|
|
- type: cumulative_normalized_distance_until_tree_drop
|
|
value: 0.13179252222180365 +/- 0.02826017752675318
|
|
name: Cumulative Normalized Distance Until Tree Drop
|
|
verified: true
|
|
- type: cumulative_tree_drop_reward
|
|
value: 4.009531931877136 +/- 0.661158168654566
|
|
name: Cumulative Tree Drop Reward
|
|
verified: true
|
|
- type: out_of_energy_count
|
|
value: 0.03808173710480332 +/- 0.021781055433560147
|
|
name: Out of Energy Count
|
|
verified: true
|
|
- type: recharge_energy_count
|
|
value: 10.746735401153565 +/- 0.6862137746749559
|
|
name: Recharge Energy Count
|
|
verified: true
|
|
- type: tree_drop_count
|
|
value: 0.9473729825019837 +/- 0.03268839810742225
|
|
name: Tree Drop Count
|
|
verified: true
|
|
- type: cumulative_reward
|
|
value: 101.15483459472657 +/- 3.824644657818079
|
|
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>5</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Drone-Based Reforestation**<br>Task: <code>3</code><br>Difficulty: <code>5</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) |