Spacetime Emergence in the Memory of a Learning Agent

The paper demonstrates that a model‑based reinforcement‑learning agent can learn the causal structure of Minkowski spacetime solely from maximizing quantum mutual information between localized probes, without explicit knowledge of the metric. During training, the agent builds an internal predictive model whose planner develops the null structure characteristic of spacetime, enabling accurate reconstruction of the causal structure. This result suggests that spacetime concepts can emerge from an agent’s operational quantum experience.

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