Authors:
Éric Piette, Matthew Stephenson, Dennis J. N. J. Soemers, Chiara Sironi, Mark H. M. Winands, Cameron Browne

Venue:
Conférence Nationale en Intelligence Artificielle (CNIA), 2019

Topics:
General Game Playing, Ludii, game description languages, knowledge representation, machine learning

Links: PDF · Proceedings (CNIA 2019)

While current General Game Playing (GGP) systems facilitate useful research in Artificial Intelligence (AI) for game-playing, they are often somewhat specialized and computationally inefficient.

In this paper, we describe an initial version of a ?ludemic? general game system called LUDII, which has the potential to provide an efficient tool for AI researchers as well as game designers or historians and practitioners in related fields.

LUDII defines games as structures of ludemes, i.e. high-level, easily understandable game concepts. We establish the foundations of LUDII by outlining its main benefits: generality, extensibility, understandability and efficiency. Experimentally, LUDII outperforms one of the most efficient Game Description Language (GDL) reasoners, based on a propositional network, for all available games in the GGP repository.

Piette, É., Stephenson, M., Soemers, D. J. N. J., Sironi, C., Winands, M. H. M., Browne, C. (2019). LUDII - Le Système Ludémique de General Game Playing. Conférence Nationale en Intelligence Artificielle (CNIA).

@inproceedings{piette2019ludii_cnia,
  author    = {Piette, Éric and Stephenson, Matthew and Soemers, Dennis J. N. J. and Sironi, Chiara and Winands, Mark H. M. and Browne, Cameron},
  title     = {LUDII - Le Système Ludémique de General Game Playing},
  booktitle = {Conférence Nationale en Intelligence Artificielle (CNIA)},
  year      = {2019}
}