WallZero: Mastering the Game of WallGo with Strategic Analysis
For the WallGo community, this work provides a strong AI agent and strategic insights into a new game, though it is incremental as it applies existing AlphaZero methods with tailored features.
WallZero, an AlphaZero-based agent, defeats two professional Go players in WallGo, securing on average 1.98x more territory per game, and reveals that the Netflix series' opening yields a more balanced game.
WallGo is a recently introduced strategic board game popularized by the 2025 Netflix series The Devil's Plan. Although played on a small 7 x 7 board, its combination of stone movement and wall placement yields high game-tree complexity and intricate strategic interactions. Despite its growing popularity, WallGo remains underexplored. This paper presents WallZero, an AlphaZero-based agent for the two-player WallGo setting. We introduce tailored action and feature designs to improve playing performance significantly. In the evaluation, WallZero defeats two professional Go players who participated in this study, securing on average 1.98x more territory per game. Beyond its strength, we use WallZero to assess game fairness and identify key strategies for mastering WallGo. Interestingly, our results show that the opening used in the Netflix series yields a more balanced game. Our code is available at https://rlg.iis.sinica.edu.tw/papers/wallzero.