Training Management
Monitor, control, and optimize Q-Learning training processes
Penting - Guidelines Training AI:
- Backup Data: Pastikan backup database sebelum training intensif
- Resource Monitor: Training dapat menggunakan CPU tinggi (5-20 menit)
- Data Requirement: Minimal 10 students dan 5 states untuk hasil optimal
- Browser Stability: Jangan tutup browser selama training berlangsung
- Parameter Tuning: Gunakan default settings untuk pertama kali
Training Status
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Trained Students
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Active States
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Last Training
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Advanced Training
Untuk pengguna experiencedBatch Operations
Performance Metrics
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Training Parameters Configuration
Current Parameters
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Parameter Guidelines
Learning Rate (α):
- 0.01-0.05: Conservative learning
- 0.1-0.2: Standard learning (recommended)
- 0.3-0.5: Aggressive learning
Discount Factor (γ):
- 0.1-0.5: Short-term focus
- 0.6-0.9: Balanced (recommended)
- 0.9-0.99: Long-term focus
Episodes:
- 50-150: Fast training, basic patterns
- 200-500: Optimal convergence
- 500+: Risk of overfitting
Training Logs
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