Improving Automated Video Game Testing via Machine Learning

Complex gaming environments are laborious to create. Especially demanding tasks are manual game testing, continuous game updating of content and code, balancing of games, anomaly detection and toxic player/bot detection. Beyond high time consumption, manual testing and one-off game development may lead to shallow user models and lacking personalization which again result in low retention, missing revenue potential and poor player experiences. Freeing up game developers’ time normally spent for such tasks, may further create room for more productive creative design.
The task of this industrial PhD will be to help modl.ai create the next generation of AI personas, that can model players and allow continuous game testing at unprecedented speed.