This model serves as the baseline for the Drone-Based Reforestation environment, trained and tested on task 0 with difficulty 5 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Drone-Based Reforestation
Task: 0
Difficulty: 5
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-5

Drone-Based Reforestation

Collection

70 items • Updated 9 days ago

Evaluation results

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

2.7580876886844634 +/- 0.7562888045399391
Cumulative Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

78.29452056884766 +/- 14.296043451183179
Cumulative Distance to Existing Trees on hivex-drone-based-reforestation
self-reported

50.473754501342775 +/- 11.98073606874106
Cumulative Normalized Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

0.2758087694644928 +/- 0.07562888371330763
Cumulative Tree Drop Reward on hivex-drone-based-reforestation
self-reported

7.088011031150818 +/- 1.7168094182484812
Out of Energy Count on hivex-drone-based-reforestation
self-reported

0.9958095240592957 +/- 0.022119619288807686
Recharge Energy Count on hivex-drone-based-reforestation
self-reported

9.258539686203003 +/- 0.587428694662249
Tree Drop Count on hivex-drone-based-reforestation
self-reported

0.9893650794029236 +/- 0.03160683668166852
Cumulative Reward on hivex-drone-based-reforestation
self-reported

10.612933225631714 +/- 2.659049482325796

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