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hivex-DBR-PPO-baseline-task-5-difficulty-10

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 5 with difficulty 10 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Drone-Based Reforestation
Task: 5
Difficulty: 10
Algorithm: PPO
Episode Length: 2000
Training max_steps: 1200000
Testing max_steps: 300000

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Collection including hivex-research/hivex-DBR-PPO-baseline-task-5-difficulty-10

Evaluation results

  • Highest Point on Terrain Found on hivex-drone-based-reforestation
    self-reported
    46.44914810180664 +/- 4.140176869643727
  • Out of Energy Count on hivex-drone-based-reforestation
    self-reported
    0.6642222416400909 +/- 0.0670919881726494
  • Cumulative Reward on hivex-drone-based-reforestation
    self-reported
    45.629833755493166 +/- 3.45321067867071
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