General Video Game AI: a Multi-Track Framework for Evaluating Agents,
  Games and Content Generation Algorithms
  General Video Game Playing (GVGP) aims at designing an agent that is capable
of playing multiple video games with no human intervention. In 2014, The
General Video Game AI (GVGAI) competition framework was created and released
with the purpose of providing researchers a common open-source and easy to use
platform for testing their AI methods with potentially infinity of games
created using Video Game Description Language (VGDL). The framework has been
expanded into several tracks during the last few years to meet the demand of
different research directions. The agents are required either to play multiple
unknown games with or without access to game simulations, or to design new game
levels or rules. This survey paper presents the VGDL, the GVGAI framework,
existing tracks, and reviews the wide use of GVGAI framework in research,
education and competitions five years after its birth. A future plan of
framework improvements is also described.
