人类首次接触新游戏时，靠快速浅层模拟实现灵活决策。
People use fast and flat simulation to reason about new games
- 用快速浅层的模拟机制解释人类如何快速理解新游戏
- 1000+参与者在121个全新棋类游戏中表现出系统性适应策略
- 适合研究人类认知灵活性与人机共融AI设计
游戏长期以来是研究自然与人工智能中规划与推理的微型模型，传统研究聚焦于专家级或超人类表现。但现实生活中，人类还需灵活应对从未遇见过的新问题。本文通过大规模行为实验（超过1000名参与者，121种对参与者而言几乎全新的双人策略棋类游戏），发现人们在首次接触游戏或未实际游玩前，即可系统性且自适应地评估游戏的公平性、趣味性等特征。我们提出一种名为‘直觉玩家’（Intuitive Gamer）的计算认知模型，其基于深度受限的、目标导向的概率模拟机制，解释了这种快速推理能力。该研究揭示了人类在面对新问题时的快速评估、行动与建议生成机制，为设计更灵活、更贴近人类思维的智能系统提供了新思路，使AI不仅能解决新任务，还能判断任务是否值得投入思考。
原文摘要 · Abstract (English)
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.
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