General video game AI: A multitrack framework for evaluating agents, games, and content generation algorithms

Diego Perez-Liebana, Jialin Liu, Ahmed Khalifa, Raluca D. Gaina, Julian Togelius, Simon M. Lucas

    Research output: Contribution to journalArticlepeer-review


    General video game playing aims at designing an agent that is capable of playing multiple video games with no human intervention. In 2014, the General Video Game Artificial Intelligence (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 artificial intelligence (AI) methods with potentially infinity of games created using the video game description language (VGDL). The framework has been expanded into several tracks during the last few years to meet the demands 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.

    Original languageEnglish (US)
    Article number2901021
    Pages (from-to)195-214
    Number of pages20
    JournalIEEE Transactions on Games
    Issue number3
    StatePublished - Sep 2019


    • Artificial intelligence
    • Computational intelligence
    • Games
    • General Video Game AI (GVGAI)
    • General video game playing (GVGP)
    • Video game description language (VGDL)

    ASJC Scopus subject areas

    • Software
    • Control and Systems Engineering
    • Artificial Intelligence
    • Electrical and Electronic Engineering


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