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This model serves as the baseline for the Drone-Based Reforestation environment, trained and tested on task 3 with difficulty 10 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Drone-Based Reforestation
Task: 3
Difficulty: 10
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

1.3822244083881379 +/- 0.2799904225640544
Cumulative Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

49.66127479553223 +/- 7.218445332813338
Cumulative Distance to Existing Trees on hivex-drone-based-reforestation
self-reported

65.08539611816406 +/- 5.7159717268853285
Cumulative Normalized Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

0.13822243928909303 +/- 0.027999042034590665
Cumulative Tree Drop Reward on hivex-drone-based-reforestation
self-reported

4.014332270622253 +/- 0.740893757159681
Out of Energy Count on hivex-drone-based-reforestation
self-reported

0.03652440816164017 +/- 0.02224060499692208
Recharge Energy Count on hivex-drone-based-reforestation
self-reported

10.598072090148925 +/- 0.5897619835270185
Tree Drop Count on hivex-drone-based-reforestation
self-reported

0.9516399455070496 +/- 0.03216850980609787
Cumulative Reward on hivex-drone-based-reforestation
self-reported

101.69934463500977 +/- 3.379470856148503

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