用博弈论建模多智能体心智理论，实现可计算的理性决策。
A Computable Game-Theoretic Framework for Multi-Agent Theory of Mind
- 基于博弈论构建可计算的心智理论框架
- 支持有限理性下的递归信念推理
- 适合研究多智能体协作与博弈的学者
源自心理学的‘心智理论’（Theory of Mind, ToM）在逻辑、经济和机器人学等多个领域受到广泛关注。尽管心理学研究未试图形式化目标、意图和信念等核心概念以实现自动化计算过程，但逻辑学家已对此进行了深入探讨。本文提出一种新的视角：从博弈论出发，构建一个计算框架。该框架既规定了在保持对他人心智理解的同时做出有限理性决策的方法（包括递归地理解他人对彼此心智的理解），又通过统计技术与近似解法确保内在计算问题的可计算性。
原文摘要 · Abstract (English)
Originating in psychology, $\textit{Theory of Mind}$ (ToM) has attracted significant attention across multiple research communities, especially logic, economics, and robotics. Most psychological work does not aim at formalizing those central concepts, namely $\textit{goals}$, $\textit{intentions}$, and $\textit{beliefs}$, to automate a ToM-based computational process, which, by contrast, has been extensively studied by logicians. In this paper, we offer a different perspective by proposing a computational framework viewed through the lens of game theory. On the one hand, the framework prescribes how to make boudedly rational decisions while maintaining a theory of mind about others (and recursively, each of the others holding a theory of mind about the rest); on the other hand, it employs statistical techniques and approximate solutions to retain computability of the inherent computational problem.
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