This model serves as the baseline for the Drone-Based Reforestation environment, trained and tested on task 0 with difficulty 10 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Drone-Based Reforestation
Task: 0
Difficulty: 10
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-10

Drone-Based Reforestation

Collection

70 items • Updated 10 days ago

Evaluation results

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

2.4901976776123047 +/- 0.7106346342581482
Cumulative Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

73.15180267333984 +/- 16.01239171149343
Cumulative Distance to Existing Trees on hivex-drone-based-reforestation
self-reported

59.689389877319336 +/- 11.847134878664495
Cumulative Normalized Distance Until Tree Drop on hivex-drone-based-reforestation
self-reported

0.2490197652578354 +/- 0.07106346368414662
Cumulative Tree Drop Reward on hivex-drone-based-reforestation
self-reported

6.189901051521301 +/- 2.069236630928566
Out of Energy Count on hivex-drone-based-reforestation
self-reported

0.9284761929512024 +/- 0.0666754640473818
Recharge Energy Count on hivex-drone-based-reforestation
self-reported

9.823968200683593 +/- 1.0843417843839367
Tree Drop Count on hivex-drone-based-reforestation
self-reported

1.0422539913654327 +/- 0.06928386006526491
Cumulative Reward on hivex-drone-based-reforestation
self-reported

10.091075601577758 +/- 2.9491417551616106

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