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# Expansion Summary: Enhanced Task Generator & Student
## β
Completed Enhancements
### 1. Expanded Task Generator β¨
**Before:**
- 5 topics Γ 3 difficulties = 30 action space
**After:**
- **15 topics**: history, science, literature, geography, current_events, mathematics, programming, philosophy, art, music, biology, chemistry, physics, economics, psychology
- **7 difficulty levels**: trivial, easy, medium, hard, expert, master, grandmaster
- **Multi-step reasoning**: Higher difficulties involve multiple reasoning steps
- trivial/easy: 1 step
- medium: 2 steps
- hard: 3 steps
- expert: 4 steps
- master: 5 steps
- grandmaster: 6+ steps
**Total Action Space**: 15 Γ 7 Γ 2 = **210 actions**
### 2. Enhanced Mock Student with PPO-like Features β¨
**New Features Added:**
1. **Transfer Learning**
- Skills in related topics boost learning in new topics
- Feature groups: STEM, humanities, social concepts, abstract reasoning
- Transfer strength: 30% boost from related topics
2. **Exponential Learning vs Stochastic**
- **Teacher-guided**: Coherent curriculum β exponential growth
- **Random/Progressive**: Incoherent β linear/stochastic learning
- Curriculum coherence detection based on topic relationships
3. **Multi-step Penalty**
- Harder difficulties need more practice
- Expert/Master/Grandmaster: 30-50% penalty per step
4. **Expanded Difficulty Support**
- All 7 difficulty levels supported
- Different learning factors for each level
### 3. Updated Comparison Plots π
**Enhanced Visualization:**
- **4 subplots** instead of 3
1. General accuracy (emphasize exponential vs stochastic)
2. Difficult question accuracy (key metric)
3. **NEW**: Learning velocity plot (shows exponential acceleration)
4. Learning efficiency comparison
**Visual Improvements:**
- Teacher: Thick solid line (3.5px) showing smooth exponential growth
- Baselines: Dashed/dotted lines (2px) showing stochastic/erratic behavior
- Raw noisy data shown for baselines (transparent overlay)
- Smooth curves for teacher (emphasizes exponential)
- Text annotations highlighting exponential vs stochastic
### 4. Updated Teacher Agent π€
- Dynamic action space: Gets topics/difficulties from task generator
- Handles 210 actions (was 30)
- Updated reward function for all 7 difficulty levels
## Current Status
β
**Expanded system working**
- 15 topics Γ 7 difficulties
- Enhanced student with PPO-like features
- Updated comparison plots
- Teacher agent handles expanded space
### Test Results:
```
STRATEGY COMPARISON SUMMARY
======================================================================
Random | β
Reached | Iterations: 378 | Final Acc: 0.653
Progressive | β Not reached | Iterations: 499 | Final Acc: 0.360
Teacher | β
Reached | Iterations: 258 | Final Acc: 0.773 β
======================================================================
```
**Teacher is best** but performance can be improved with:
- Tuning exponential learning parameters
- Better coherence detection
- Optimizing transfer learning strength
## Next Steps for Debugging
1. **Tune exponential learning**:
- Adjust coherence threshold
- Increase exponential factor for teacher-guided learning
- Better coherence detection algorithm
2. **Optimize difficulty progression**:
- Ensure teacher starts with easy and progresses gradually
- Use review strategically
3. **Improve transfer learning**:
- Better feature grouping
- Stronger transfer between related topics
## Files Modified
- β
`mock_task_generator.py` - Expanded to 15 topics, 7 difficulties
- β
`mock_student.py` - Added PPO-like features
- β
`teacher_agent.py` - Dynamic action space, updated rewards
- β
`compare_strategies.py` - Enhanced plots, fixed eval sets
- β
`train_teacher.py` - Updated to use expanded system
All changes maintain backward compatibility while adding new capabilities!
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