Where 'Solvable' and 'Fun' Diverge — PuzzleJAX Hands 500+ PuzzleScript Games to the Machines (arXiv, Aug 2025)

Letting an LLM build a whole game, and an AI playtest it: ScriptDoctor and the state of automatic game design

One piece today. I read, in the original English, "ScriptDoctor: Automatic Generation of PuzzleScript Games via Large Language Models and Tree Search" by Sam Earle, Julian Togelius and colleagues (arXiv:2506.06524; a short paper submitted to the IEEE Conference on Games). They pick PuzzleScript — the description language for turn-based 2D-grid puzzle games created by increpare (Stephen Lavelle) — as a "model organism," and have an LLM generate a whole game (rules, sprites, levels), iterating on it using compiler errors and the results of a breadth-first-search player agent. Feeding in a few human-authored games as examples clearly raises quality, and reasoning models (o1, o3-mini) beat GPT-4o. But the sharpest lesson is on the failure side: the games that looked most complex were often complex only because of broken mechanics — solvable is not the same as good. A rich read for anyone thinking about automatic game design.