teacher_agent_dev/RANDOMNESS_GUIDE.md

Randomness Configuration Guide

Quick Answer to Your Question

Yes, it's fine to have randomness! By default, the script now uses random seeds, so results will vary each run. This is actually better because it shows the true stochastic nature of learning.

How It Works Now

Default Behavior (Random - Results Vary)

python compare_strategies.py

• Uses current time as seed
• Results will be different each run
• Better for seeing variance and stochasticity

Deterministic Mode (Same Results Every Time)

python compare_strategies.py --deterministic

• Uses fixed seed=42
• Results will be identical every run
• Good for debugging and reproducibility

Variance Analysis (Multiple Runs)

python compare_strategies.py --runs 10

• Runs 10 times with different seeds
• Shows mean ± standard deviation
• Best for robust evaluation

Why This Matters

The learning process has natural randomness:

• Random strategy: Obviously random! 🎲
• Student learning: Stochastic answers (probabilistic)
• Teacher strategy: RL exploration adds variance

Seeing this variance is important because:

1. Single runs can be lucky/unlucky
2. Variance shows robustness (lower variance = more reliable)
3. Real-world performance will vary

Example: Seeing the Difference

Run 1:

Teacher: Final Acc: 0.773
Random:  Final Acc: 0.653

Run 2 (different seed):

Teacher: Final Acc: 0.789
Random:  Final Acc: 0.641

Run 3 (different seed):

Teacher: Final Acc: 0.761
Random:  Final Acc: 0.667

This variance is normal and expected! The teacher should still outperform on average.

Best Practices

1. For development/testing: Use --deterministic for consistent debugging
2. For evaluation: Use --runs 10 to see robust statistics
3. For quick checks: Default (random) is fine - just run multiple times manually

All Options

python compare_strategies.py [OPTIONS]

Options:
  --seed SEED          Use specific seed (e.g., --seed 123)
  --deterministic      Use seed=42 (reproducible, same every time)
  --iterations N       Train for N iterations (default: 500)
  --runs N             Run N times for variance analysis

Summary

✅ Default now has randomness - results vary (this is good!) ✅ Use --deterministic if you want identical results ✅ Use --runs N for proper variance analysis ✅ Variance is expected - shows realistic behavior

The stochastic nature is actually a feature, not a bug! It shows the true variability in learning.