Evaluation of a Recommender System for Assisting Novice Game Designers


  • Tiago Machado New York University
  • Daniel Gopstein New York University
  • Angela Wang New York University
  • Oded Nov New York University
  • Andrew Nealen University of Southern California
  • Julian Togelius New York University


Game development is a complex task involving multiple disciplines and technologies. Developers and researchers alike have suggested that AI-driven game design assistants may improve developer workflow. We present a recommender system for assisting humans in game design as well as a rigorous human subjects study to validate it. The AI-driven game design assistance system suggests game mechanics to designers based on characteristics of the game being developed. We believe this method can bring creative insights and increase user’s productivity. We conducted quantitative studies that showed the recommender system increases users’ levels of accuracy and computational affect, and decreases their levels of workload.




How to Cite

Machado, T., Gopstein, D., Wang, A., Nov, O., Nealen, A., & Togelius, J. (2019). Evaluation of a Recommender System for Assisting Novice Game Designers. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 15(1), 167-173. Retrieved from https://ojs.aaai.org/index.php/AIIDE/article/view/5240