Emergent social transmission of model-based representations without inference
How do people acquire rich, flexible knowledge about their environment from others despite limited cognitive capacity? Humans are often thought to rely on computationally costly mentalizing, such as inferring others' beliefs. In contrast, cultural evolution emphasizes that behavioral transmission can be supported by simple social cues. Using reinforcement learning simulations, we show how minimal social learning can indirectly transmit higher-level representations. We simulate a naïve agent searching for rewards in a reconfigurable environment, learning either alone or by observing an expert - crucially, without inferring mental states. Instead, the learner heuristically selects actions o...
| Authors | Silja Keßler, Miriam Bautista-Salinero, Claudio Tennie et al. |
|---|---|
| Primary category | cs.AI |
| Published | 7 April 2026 |
| Last updated at source | 8 May 2026 |
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