People Use Fast and Flat Simulation to Reason About New Games

Jul 16, 2026

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Games serve as a testing ground for planning and reasoning in natural and artificial intelligence, yet everyday decisions often involve novel settings rather than expert-level play. This work uses novice gameplay to study how people reason about unfamiliar game rules through large-scale behavioral studies with 1000+ participants and 121 two-player strategic board games. Findings show adaptive rationality and systematic reasoning for first-time play and for evaluating a game’s likely fairness or fun. A computational cognitive model, “Intuitive Gamer,” explains these behaviors via fast, depth-limited probabilistic simulation and informs flexible human-like AI design.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages82

Reading Time3 h 27 min

Abstract

Background: Games as reasoning testbeds

Novice game reasoning study design

Game evaluation

Action selection

Action prediction

Computational cognitive model: Intuitive Gamer

Implications for AI and decision-making

arXiv :2510 . 11503v2 [ q-bio .NC] 12 Jul 2026 People use fast and flat simulation to reason about new games Katherine M. Collins*†1,2,3, Cedegao E. Zhang† 1, Lionel Wong† 1,4, Mauricio Barba da Costa†1, Graham Todd†5, Adrian Weller3,6, Samuel J. Cheyette1, Thomas L. Griffiths2, and Joshua B. Tenenbaum1 1Massachusetts Institute of Technology, Cambridge, MA, United States 2Princeton University, Princeton, NJ, United States 3University of Cambridge, Cambridge, United Kingdom 4Stanford University, Stanford, CA, United States 5New York University, New York City, NY, United States 6The Alan Turing Institute, London, United Kingdom †indicates equal contributions. 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 (1, 2, 3, 4, 5, 6) . 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 offast 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. Games occupy a special space in psychology and and computer science (7, 8, 9, 1, 2, 3, 10, 4, 11, 12, 6) for good reason: games are systems of rules and reward that hold a mirror to the structures, patterns and challenges that reality confronts us with, across familiar and merely possible experiences. Mancala lets us sow and capture abstract resources. Chess lets us strategize over bloodless battlefields. Go lets us encircle and claim territories with silent stone troops. A good game lets us thrill to uncertainties and losses that we might shy from in real life. Substantial work in cognitive science focuses on the nature and development of expertise, using games as a testbed (13, 3, 6) . Human experts, correspondingly, have long served as goalposts in the quest to build intelligent machines, with a particular focus on emulating and ultimately beating humans at their own games, using more game-playing data and raw computational horsepower than any human expert could acquire in their lifetimes (2, 4, 14, 15) . But people are not experts at most of the problems they encounter throughout their lives, or most systems they are thrown into before they need to decide on an action. Human cognition is flexible enough to consider many potential problems, and many potential systems of rule * Corresponding author: [katiemc@mit.edu](katiemc@mit.edu) a 4x4 3 in a row wins 7x7 1st player needs 4 in a row; 2nd player needs 3 in a row b Game evaluation 5x5 5 in a row wins 5x5 4 in a row wins. 2nd player opens twice. 4x6 4 in a row wins 4x4 3 in a row wins. Only diagonals win. Infinity x Infinity 3 in a row wins ... ... ...... 4x4 3 in a row wins. 1st player only wins on diagonals c d Action selection 3x3 board, 3 in a row wins. 2nd player opens twice. If this game does not end in a draw, how likely is it that the first player wins? 0% 50% 100% 3x3 board, 3 in a row wins. 2nd player opens twice. 5x5

FAQs

How does the paper study reasoning about new games?

It uses novice gameplay in large-scale behavioral studies with 1000+ participants and 121 novel two-player strategic board games, measuring how people evaluate games, choose actions, and predict others’ moves.

What evidence is used to show people’s reasoning is systematic and adaptively rational?

Participants’ behavior across first-time play and prior evaluation tasks is analyzed to demonstrate systematic, adaptive rationality in how they reason under unfamiliar rules.

What model explains the observed reasoning abilities?

The “Intuitive Gamer” computational cognitive model explains behavior using fast, depth-limited (“fast and flat”) goal-directed probabilistic simulation, linking cognitive mechanisms to observed choices and judgments.

Jul 16, 2026

Upload by Patrick