Automated Game Design via Conceptual Expansion


  • Matthew Guzdial Georgia Institute of Technology
  • Mark Riedl Georgia Institute of Technology



automated game design, machine learning, computational creativity


Automated game design has remained a key challenge within the field of Game AI. In this paper, we introduce a method for recombining existing games to create new games through a process called conceptual expansion.Prior automated game design approaches have relied on hand-authored or crowd-sourced knowledge, which limits the scope and applications of such systems. Our approach instead relies on machine learning to learn approximate representations of games. Our approach recombines knowledge from these learned representations to create new games via conceptual expansion.We evaluate this approach by demonstrating the ability for the system to recreate existing games. To the best of our knowledge, this represents the first machine learning-based automated game design system.




How to Cite

Guzdial, M., & Riedl, M. (2018). Automated Game Design via Conceptual Expansion. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 14(1), 31-37.