My thesis project is a game which constantly transforms itself for each player. It does so by ‘understanding’ players through their gameplay and designs itself in such a way that each player gets a unique, personalized and optimal experience every time they play the game. The purpose of doing so is to cater to the diverse needs of players and tailor the game based on their skills and preferences. The game in question is Monkey Swing, which is a web-based, color-matching, memory game to develop Executive Functions (E.F).
Process Overview: Data logs generated through gameplay are analyzed and stored into a persistent learner model residing on an external database. A data stream runs from the learner model to the adaptation engine which constantly analyzes the data to generate content blueprints, these blueprints are updated frequently as more data is received from the learner model database . When the game engine needs to create more content it asks the adaptation engine for updates. The adaptation engine, in response to the query, sends the most recent content blueprint. The game engine then materializes the content blueprint into game content.