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hivex-DBR-PPO-baseline-task-4-difficulty-1

Reinforcement Learning
TensorBoard
ONNX
hivex
hivex-drone-based-reforestation
multi-agent-reinforcement-learning
Eval Results
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This model serves as the baseline for the Drone-Based Reforestation environment, trained and tested on task 4 with difficulty 1 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Drone-Based Reforestation
Task: 4
Difficulty: 1
Algorithm: PPO
Episode Length: 2000
Training max_steps: 1200000
Testing max_steps: 300000

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Evaluation results

  • Highest Potential Soild Found on hivex-drone-based-reforestation
    self-reported
    0.9788281238079071 +/- 0.032543043270812776
  • Out of Energy Count on hivex-drone-based-reforestation
    self-reported
    0.6642222416400909 +/- 0.0670919881726494
  • Cumulative Reward on hivex-drone-based-reforestation
    self-reported
    -0.01776815608205652 +/- 0.022001924051183442
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