Readable Minds: Emergent Theory-of-Mind-Like Behavior in LLM Poker Agents
Theory of Mind (ToM) -- the ability to model others' mental states -- is fundamental to human social cognition. Whether large language models (LLMs) can develop ToM has been tested exclusively through static vignettes, leaving open whether ToM-like reasoning can emerge through dynamic interaction. Here we report that autonomous LLM agents playing extended sessions of Texas Hold'em poker progressively develop sophisticated opponent models, but only when equipped with persistent memory. In a 2x2 factorial design crossing memory (present/absent) with domain knowledge (present/absent), each with five replications (N = 20 experiments, ~6,000 agent-hand observations), we find that memory is bot...
| Authors | Hsieh-Ting Lin, Tsung-Yu Hou |
|---|---|
| Primary category | cs.AI |
| Published | 5 April 2026 |
| Last updated at source | 5 April 2026 |
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