2048 N-Tuple Network Model
Trained using TD(0) afterstate learning with 8 six-tuple patterns and 8 symmetries.
Stats
- Games trained: 1,200,000
- Max tile reached: 16384
- Patterns: 8 six-tuples with 8 symmetry transforms each
- Weight table size: ~347 MB
Files
weights.bin - raw Float32 weight tables (8 x 11390625 floats)config.json - model architecture and training metadatapatterns.json - tuple pattern definitions
Usage
Load the binary weights into 8 Float32Arrays of size 11390625 each.
For each board state, compute the feature index for each pattern under all 8 symmetries
and sum the corresponding weight values to get the board evaluation score.
Pick the move whose afterstate has the highest (reward + evaluation).
