GoKawiilDrop7 AI project reports learned evaluator beating fair-leaf search in screen-tier test, replicated twice
A hobbyist research log on the Drop7 puzzle game describes a learned evaluator — lookup tables trained via temporal-difference self-play for four billion moves — outperforming a 'fair leaf' baseline inside the same depth-3 search. In a 256-game test it scored 484,577 points to 314,438, and the result replicated on a separate 512-game block on 2026-09-06 with a verified identical model, scoring 487,066 to 326,717.