Tile Based

Tile-based game level generation is a burgeoning field focused on automating the creation of levels for 2D games, aiming to improve efficiency and explore design spaces. Current research emphasizes the use of machine learning, particularly neural networks (including autoencoders and convolutional networks) and reinforcement learning, often coupled with genetic algorithms or Markov models, to generate, balance, and style-transfer levels. These techniques are applied to diverse tasks such as upscaling level resolution, creating levels from text prompts, and automatically balancing competitive gameplay. This research contributes to both procedural content generation and AI-assisted game design, offering tools for game developers and providing insights into creative processes.