TOWARD A CAUSAL MODEL FOR AUTOMATIC GAME BALANCING

摘要

We have started to develop a mathematical model of how various aspects of a computer game influence how much fun it is to play. This causal model is organized into three layers: a generic layer that applies to any game, a refinement layer for a particular game genre, and an instantiation layer for a specific game. We have conducted an initial user study to validate the model using a simple sports game called Slime Volleyball. In addition to providing insight into game design, our causal model is intended to provide a foundation for the application of machine learning and optimization techniques to improve the player's experience.