An Empirical Evaluation of Two General Game Systems: Ludii and RBG
This work provides a comparative analysis for researchers in AI game-playing, though it appears incremental as it evaluates recently emerged systems without introducing new methods.
This paper empirically evaluates two new general game systems, Ludii and RBG, comparing them in terms of simplicity/clarity and efficiency to address the computational inefficiency and specialization issues in existing GGP systems like GDL.
Although General Game Playing (GGP) systems can facilitate useful research in Artificial Intelligence (AI) for game-playing, they are often computationally inefficient and somewhat specialised to a specific class of games. However, since the start of this year, two General Game Systems have emerged that provide efficient alternatives to the academic state of the art -- the Game Description Language (GDL). In order of publication, these are the Regular Boardgames language (RBG), and the Ludii system. This paper offers an experimental evaluation of Ludii. Here, we focus mainly on a comparison between the two new systems in terms of two key properties for any GGP system: simplicity/clarity (e.g. human-readability), and efficiency.