Blood bowl: A new board game challenge and competition for AI

Niels Justesen, Lasse Møller Uth, Christopher Jakobsen, Julian Togelius, Sebastian Risi

    Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

    Abstract

    We propose the popular board game Blood Bowl as a new challenge for Artificial Intelligence (AI). Blood Bowl is a fully-observable, stochastic, turn-based, modern-style board game with a grid-based playing board. At first sight, the game ought to be approachable by numerous game-playing algorithms. However, as all pieces on the board belonging to a player can be moved several times each turn, the turn-wise branching factor becomes overwhelming for
    traditional algorithms. Additionally, scoring points in the game is rare and difficult, which makes it hard to design heuristics for search algorithms or apply reinforcement learning. We present our work in progress on a game engine that implements the core rules of Blood Bowl with a forward model and a reinforcement learning interface. We plan to release the engine as open source and use it to facilitate future AI competitions.
    OriginalsprogEngelsk
    Titel2019 IEEE Conference on Games (CoG)
    Antal sider8
    ForlagIEEE
    Publikationsdato2019
    Sider1-8
    ISBN (Elektronisk)123-4567-24-567/08/06.
    DOI
    StatusUdgivet - 2019

    Emneord

    • Blood Bowl
    • Artificial Intelligence
    • Stochastic games
    • Turn-based strategy
    • Reinforcement learning

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