Deep learning for video game playing

Niels Justesen, Philip Bontrager, Julian Togelius, Sebastian Risi

    Research output: Contribution to journalArticlepeer-review


    In this paper, we review recent deep learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games. We analyze the unique requirements that different game genres pose to a deep learning system and highlight important open challenges in the context of applying these machine learning methods to video games, such as general game playing, dealing with extremely large decision spaces and sparse rewards.

    Original languageEnglish (US)
    Article number2896986
    Pages (from-to)1-20
    Number of pages20
    JournalIEEE Transactions on Games
    Issue number1
    StatePublished - Mar 2020


    • Algorithms
    • Artificial intelligence
    • Learning
    • Machine learning algorithms
    • Multilayer neural network

    ASJC Scopus subject areas

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


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