This model serves as the baseline for the Drone-Based Reforestation environment, trained and tested on task 0 with difficulty 9 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Drone-Based Reforestation
Task: 0
Difficulty: 9
Algorithm: PPO
Episode Length: 2000
Training max_steps: 1200000
Testing max_steps: 300000

Train & Test Scripts
Download the Environment

Downloads last month: -; Downloads are not tracked for this model. How to track

Video Preview

Reinforcement Learning

Collection including hivex-research/hivex-DBR-PPO-baseline-task-0-difficulty-9

Drone-Based Reforestation

Collection

70 items • Updated 10 days ago

Evaluation results

Cumulative Distance Reward on hivex-drone-based-reforestation
self-reported

1.9881950914859772 +/- 0.6435197796866906
Cumulative Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

62.70152519226074 +/- 15.481708378361306
Cumulative Distance to Existing Trees on hivex-drone-based-reforestation
self-reported

65.97381935119628 +/- 11.85813603247749
Cumulative Normalized Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

0.19881950929760933 +/- 0.06435197701542571
Cumulative Tree Drop Reward on hivex-drone-based-reforestation
self-reported

5.003359270095825 +/- 1.691449588116139
Out of Energy Count on hivex-drone-based-reforestation
self-reported

0.9511428594589233 +/- 0.05597489611462524
Recharge Energy Count on hivex-drone-based-reforestation
self-reported

10.313650798797607 +/- 1.3015464035988247
Tree Drop Count on hivex-drone-based-reforestation
self-reported

1.0218095362186432 +/- 0.05570651145686611
Cumulative Reward on hivex-drone-based-reforestation
self-reported

7.543602123260498 +/- 2.5896056315352975

View on Papers With Code