Wazir Drop: a tournament winning board game AI engine (github.com)

Wazir Drop, a newly developed board game AI engine, has emerged as a noteworthy player in the AI/ML landscape after securing tournament victories. This innovative engine supports a complex game where players maneuver unique pieces with varying movement capabilities, akin to chess, but with additional strategic elements such as piece "drops" from captured opponents. The AI’s architecture utilizes reinforcement learning and an efficient neural network design (NNUE), which is key in evaluating game positions and generating optimal moves. The engine's technical foundation is built on a tailored position and move representation system, leveraging bitboards for memory efficiency and a detailed tree search algorithm to explore potential game scenarios. The training process involves self-play, where the AI refines its evaluation function through extensive game simulations, leading to a sophisticated understanding of piece value and strategy over multiple iterations. This development not only highlights advancements in game-playing AI but also showcases techniques that could be applied to enhance machine learning models across various domains in AI.