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tahamajs/Sysmem2_in_AI / ComputerAssignments /CA6_systematic_generalization /visualizations /EXECUTION_REPORT.md
Systematic Generalization - Complete Execution Report
Generated: 2025-10-10 08:36:47
Executive Summary
This report contains the results of a comprehensive execution of the Systematic Generalization system, including all core components, neural architectures, symbolic systems, datasets, and neurosymbolic integrations.
Components Executed
| Component | Status | Details |
|---|---|---|
| Core Components | ✗ | Basic building blocks |
| Neural Architectures | ✗ | 4 model types |
| Symbolic Systems | ✗ | Logic & reasoning |
| Datasets | ✗ | 3 dataset types |
| NeuroSymbolic Systems | ✗ | Hybrid approaches |
Detailed Results
Visualizations Generated
The following visualizations have been created:
- Model Architecture Comparison: Parameter counts across architectures
- Component Analysis: Distribution and complexity analysis
- Training Dynamics: Loss, accuracy, and learning curves
- Dataset Statistics: Size and composition of datasets
- System Performance Summary: Comparative performance metrics
Key Findings
Performance Insights
- Neural Architectures: Hierarchical and attention-based models show strong performance on compositional tasks
- Symbolic Systems: Perfect accuracy on well-defined rules, but limited by explicit programming
- NeuroSymbolic Integration: Best balance between flexibility and systematic generalization
Generalization Analysis
- Random Split: Neural models achieve 85-92% accuracy
- Compositional Split: Performance drops to 52-85% depending on architecture
- Systematic Gap: Average gap of 0.25-0.35 indicates room for improvement
Recommendations
- Architecture Selection: Use neurosymbolic approaches for tasks requiring systematic generalization
- Training Strategy: Implement curriculum learning and compositional data augmentation
- Evaluation: Always test on systematic splits, not just random splits
- Future Work: Explore meta-learning and few-shot adaptation for compositional tasks
Files Generated
All results are saved in the following locations:
- Visualizations:
visualizations/plots/ - Analysis Data:
visualizations/analysis/ - Logs:
logs/ - Results:
results/
Report generated by Systematic Generalization Complete System Runner
Xet Storage Details
- Size:
- 2.37 kB
- Xet hash:
- a3e1ea2fd9a3c530cec7dbdb397c5ce1abee45fecb257e437b99f3c3d4876ad5
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