Duplicate from rogermt/neurogolf-2026

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README.md

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+# NeuroGolf 2026 Submission
+
+This repository contains solutions for the 2026 NeuroGolf Championship competition on Kaggle.
+
+## Results
+
+- **Tasks solved:** 276/400 (69%)
+- **Total score:** 4106.7
+- **Average score per solved task:** 14.9
+
+## Approach
+
+The solver uses multiple strategies in order of increasing complexity:
+
+1. **Identity** - Output equals input
+2. **Color map** - Per-pixel color remapping
+3. **Transpose/Flip/Rotate** - Geometric transformations
+4. **Tiling** - Conditional Kronecker product
+5. **Upscale** - Nearest-neighbor upscaling
+6. **Concatenation patterns** - Horizontal/vertical concatenation with transforms
+7. **Position-based color LUT** - Per-position color lookup table
+8. **Spatial gather** - Pixel rearrangement
+9. **Linear/Affine** - Matrix multiplication
+10. **One-hot convolution** - Encode colors as channels, apply convolution, decode via argmax
+
+The one-hot convolution approach proved most effective, solving 220 tasks. It encodes each pixel as a 10-channel one-hot vector, applies a learned convolution, and decodes via argmax.
+
+## Solver Breakdown
+
+| Solver | Tasks |
+|--------|-------|
+| onehot_conv | 220 |
+| spatial_gather | 24 |
+| color_map | 4 |
+| concat_patterns | 4 |
+| pos_color_lut | 3 |
+| onehot_linear | 2 |
+| flip | 2 |
+| transpose | 2 |
+| upscale | 2 |
+| tiling | 1 |
+| tile_repeat | 1 |
+
+## Files
+
+- `submission.zip` - ONNX files for 276 solved tasks
+- `solve_all.py` - Main solver script
+- `ARC-AGI/` - ARC-AGI training data
+
+## Usage
+
+```bash
+python3 solve_all.py
+```
+
+This will create a `submission/` folder with ONNX files.

submission.zip

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