GAVEL: Generating Games Via Evolution and Language Models
Authors: name: Graham Todd, name: Alexander Padula, name: Matthew Stephenson, name: Éric Piette, name: Dennis J. N. J. Soemers, name: Julian Togelius

Automatically generating novel and interesting games is a complex task.
Challenges include representing game rules in a computationally workable form,
searching through the large space of potential games under most such
representations, and accurately evaluating the originality and quality of
previously unseen games. Prior work in automated game generation has largely
focused on relatively restricted rule representations and relied on
domain-specific heuristics. In this work, we explore the generation of novel
games in the comparatively expansive Ludii game description language, which
encodes the rules of over 1000 board games in a variety of styles and modes of
play. We draw inspiration from recent advances in large language models and
evolutionary computation in order to train a model that intelligently mutates
and recombines games and mechanics expressed as code. We demonstrate both
quantitatively and qualitatively that our approach is capable of generating new
and interesting games, including in regions of the potential rules space not
covered by existing games in the Ludii dataset. A sample of the generated games
are available to play online through the Ludii portal.