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

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

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


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.
Original languageEnglish
Title of host publication2019 IEEE Conference on Games (CoG)
Number of pages8
Publication date2019
ISBN (Electronic)123-4567-24-567/08/06.
Publication statusPublished - 2019


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


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