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hivex-WFC-PPO-baseline-task-1-pattern-4

Reinforcement Learning
TensorBoard
ONNX
hivex
hivex-wind-farm-control
multi-agent-reinforcement-learning
Eval Results
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This model serves as the baseline for the Wind Farm Control environment, trained and tested on task 1 with pattern 4 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Wind Farm Control
Task: 1
Pattern: 4
Algorithm: PPO
Episode Length: 5000
Training max_steps: 8000000
Testing max_steps: 8000000

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Evaluation results

  • Cumulative Reward on hivex-wind-farm-control
    self-reported
    4816.654519042969 +/- 48.309486675816395
  • Avoid Damage Reward on hivex-wind-farm-control
    self-reported
    4816.70017578125 +/- 50.83180378290865
  • Individual Performance on hivex-wind-farm-control
    self-reported
    0.0 +/- 0.0
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