Notebooks

You can find the source code for the notebooks at .

• demo_generator.ipynb Exploring different maze generation algorithms and parameters
• demo_latticemaze.ipynb Working with LatticeMaze class, visualization and solving mazes
• demo_dataset.ipynb Creating and filtering a dataset, and various output formats
• output_formats.ipynb
• forking_points.ipynb Identifying and working with decision points in maze solutions
• iterated_backfilling.ipynb Implementation of iterated backfilling as an algorithm for solving visual mazes
• profile_dataset_save_read.ipynb Profiling and optimizing dataset serialization performance
• estimate_dataset_fractions.ipynb Estimating and predicting maze generation success rates
• demo_tokenization.ipynb Legacy tokenization with MazeTokenizer and TokenizationMode
• demo_mazetokenizermodular.ipynb Using the modern MazeTokenizerModular system for tokenization