hiivelabs.com
Building a Zèrtz AI, Part 1: MCTS, Rust, and Hexagonal Symmetry
Building a Zèrtz AI involves developing a Monte Carlo Tree Search (MCTS) engine that navigates the game's complex mechanics, including mandatory captures and dynamic board topology. The implementation utilizes a Rust backend for performance, Python for orchestration, and Panda3D for rendering, with the code available on GitHub. Key challenges addressed include handling forced capture sequences and adapting to the changing adjacency graph as the board shrinks. Future enhancements may focus on optimizing the search algorithm and exploring the implications of hexagonal symmetry on the game's strategic depth.
