Authors: Mohamed Abou-Zleikha, Noor Shaker
Type: Conference paper
Conference: Tenth Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
Title: Tenth Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
Abstract: We present a demonstration of PaTux, an authoring tool for automatic design of levels in SuperTux through combining patterns. PaTux allows game designer to specify the design of their levels using patterns extracted from training level samples. The Non-negative Matrix Factorisation (NMF) method is utilised to approximate pattern and weight matrices from the training data. The patterns are visualised for designers to choose from and the changes made on the level structure are visualised in realtime. The designer can also specify the weight of each pattern permitting exploration of a wider variety. The data used to train the model can be specified by the designer, and can be a set of hand-crafted level, or the system can automatically train on a set of pre-generated level. The system also suggests variations of the designer level which can be further edited. When the designer is satisfied with the design, the system allows loading it in the game to be played.