This model serves as the baseline for the Drone-Based Reforestation environment, trained and tested on task 0 with difficulty 2 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Drone-Based Reforestation
Task: 0
Difficulty: 2
Algorithm: PPO
Episode Length: 2000
Training max_steps: 1200000
Testing max_steps: 300000

Train & Test Scripts
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Reinforcement Learning

Collection including hivex-research/hivex-DBR-PPO-baseline-task-0-difficulty-2

Drone-Based Reforestation

Collection

70 items • Updated 22 days ago

Evaluation results

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

2.830362557172775 +/- 0.8731884646965687
Cumulative Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

81.5349309539795 +/- 16.35440671615
Cumulative Distance to Existing Trees on hivex-drone-based-reforestation
self-reported

51.15435367584229 +/- 11.396382191072137
Cumulative Normalized Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

0.28303625583648684 +/- 0.0873188485354732
Cumulative Tree Drop Reward on hivex-drone-based-reforestation
self-reported

6.897729444503784 +/- 1.9902223153268046
Out of Energy Count on hivex-drone-based-reforestation
self-reported

0.9944761908054351 +/- 0.023806801146583904
Recharge Energy Count on hivex-drone-based-reforestation
self-reported

9.503872995376588 +/- 0.6012074882399382
Tree Drop Count on hivex-drone-based-reforestation
self-reported

0.9864761888980865 +/- 0.03546595715538237
Cumulative Reward on hivex-drone-based-reforestation
self-reported

9.817112922668457 +/- 2.8792400845989854

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