This model serves as the baseline for the Drone-Based Reforestation environment, trained and tested on task 0 with difficulty 7 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Drone-Based Reforestation
Task: 0
Difficulty: 7
Algorithm: PPO
Episode Length: 2000
Training max_steps: 1200000
Testing max_steps: 300000

Train & Test Scripts
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Reinforcement Learning

Evaluation results

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

3.159047532081604 +/- 0.8357707341134992
Cumulative Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

86.77309692382812 +/- 16.14500683977347
Cumulative Distance to Existing Trees on hivex-drone-based-reforestation
self-reported

47.3928982925415 +/- 9.37172991243217
Cumulative Normalized Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

0.3159047555923462 +/- 0.08357707265270713
Cumulative Tree Drop Reward on hivex-drone-based-reforestation
self-reported

7.276955466270447 +/- 1.8673272306379547
Out of Energy Count on hivex-drone-based-reforestation
self-reported

0.9944761908054351 +/- 0.02380680114658389
Recharge Energy Count on hivex-drone-based-reforestation
self-reported

9.957492036819458 +/- 0.8696697050846641
Tree Drop Count on hivex-drone-based-reforestation
self-reported

0.9822539675235749 +/- 0.03421961796573733
Cumulative Reward on hivex-drone-based-reforestation
self-reported

11.030714321136475 +/- 2.7815221104620416

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