People use fast and flat simulation to reason about new games

[Submitted on 13 Oct 2025 (v1), last revised 12 Jul 2026 (this version, v2)]

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Abstract:Games have long been a microcosm for studying planning and reasoning in both natural and artificial intelligence (AI), often focusing on expert-level or even super-human play. But real life also pushes human intelligence along a different frontier, requiring people to flexibly navigate decision-making problems that they have never thought about before. Here, we use novice gameplay to study how people reason about new problem settings. Through a series of large-scale behavioral studies with over 1000 participants and 121 two-player strategic board games (almost all novel to our participants), we show that people are systematic and adaptively rational in how they play a game for the first time, or evaluate a game (e.g., how fair or how fun it is likely to be) before they have played it even once. We explain these capacities via a computational cognitive model that we call the ‘Intuitive Gamer’, a model based on mechanisms of fast and flat (depth-limited) goal-directed probabilistic simulation. Our work offers new insights into how people rapidly evaluate, act, and make suggestions when encountering novel problems, and could inform the design of more flexible and human-like AI systems that can determine not just how to solve new tasks, but whether a task is worth thinking about at all.

Submission history

From: Katherine Collins [view email]
[v1] Mon, 13 Oct 2025 15:12:08 UTC (47,364 KB)
[v2] Sun, 12 Jul 2026 23:02:41 UTC (13,895 KB)