This model serves as the baseline for the Drone-Based Reforestation environment, trained and tested on task 3 with difficulty 1 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Drone-Based Reforestation
Task: 3
Difficulty: 1
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-3-difficulty-1

Drone-Based Reforestation

Collection

70 items • Updated 14 days ago

Evaluation results

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

1.1704939258098603 +/- 0.19094953820226412
Cumulative Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

45.521212310791014 +/- 5.629736102757813
Cumulative Distance to Existing Trees on hivex-drone-based-reforestation
self-reported

63.47206115722656 +/- 6.1461301353938405
Cumulative Normalized Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

0.11704939216375351 +/- 0.019094953655432356
Cumulative Tree Drop Reward on hivex-drone-based-reforestation
self-reported

3.866243634223938 +/- 0.8022492017418626
Out of Energy Count on hivex-drone-based-reforestation
self-reported

0.0493655932508409 +/- 0.028394293838768382
Recharge Energy Count on hivex-drone-based-reforestation
self-reported

10.92464771270752 +/- 0.6682069442874347
Tree Drop Count on hivex-drone-based-reforestation
self-reported

0.9307654321193695 +/- 0.038764458231368655
Cumulative Reward on hivex-drone-based-reforestation
self-reported

99.16041168212891 +/- 4.422805341579576

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