This model serves as the baseline for the Drone-Based Reforestation environment, trained and tested on task 0 with difficulty 1 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Drone-Based Reforestation
Task: 0
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-0-difficulty-1

Drone-Based Reforestation

Collection

70 items • Updated 14 days ago

Evaluation results

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

2.0864201402664184 +/- 0.6296944874797746
Cumulative Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

63.19091514587402 +/- 12.303839558575664
Cumulative Distance to Existing Trees on hivex-drone-based-reforestation
self-reported

61.76650863647461 +/- 13.908253887773586
Cumulative Normalized Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

0.20864201247692107 +/- 0.06296944883377423
Cumulative Tree Drop Reward on hivex-drone-based-reforestation
self-reported

5.931592869758606 +/- 1.8518746378631161
Out of Energy Count on hivex-drone-based-reforestation
self-reported

0.9266984140872956 +/- 0.06184757754397895
Recharge Energy Count on hivex-drone-based-reforestation
self-reported

10.601777839660645 +/- 1.2478378815502142
Tree Drop Count on hivex-drone-based-reforestation
self-reported

1.0418095350265504 +/- 0.08056789785926544
Cumulative Reward on hivex-drone-based-reforestation
self-reported

8.961133165359497 +/- 2.7381643935331064

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