Markov Chain Implementation for Generating Rush Hour Levels
This project involves the creation and evaluation of a procedural content generation approach designed to generate levels for a 2D, tile-based puzzle game, Rush Hour. The project leverages N-gram Markov Chain models to learn from existing level designs and generate new, playable levels that maintain the characteristics of the training dataset. This approach aims to automate the level design process, ensuring a continuous supply of fresh and engaging content for players.