A Computable Game-Theoretic Framework for Multi-Agent Theory of Mind
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866917110607773696 |
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| author | Zhu, Fengming Pan, Yuxin Zhu, Xiaomeng Lin, Fangzhen |
| author_facet | Zhu, Fengming Pan, Yuxin Zhu, Xiaomeng Lin, Fangzhen |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_22536 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Computable Game-Theoretic Framework for Multi-Agent Theory of Mind Zhu, Fengming Pan, Yuxin Zhu, Xiaomeng Lin, Fangzhen Artificial Intelligence Computer Science and Game Theory Multiagent Systems 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. |
| title | A Computable Game-Theoretic Framework for Multi-Agent Theory of Mind |
| topic | Artificial Intelligence Computer Science and Game Theory Multiagent Systems |
| url | https://arxiv.org/abs/2511.22536 |