强化学习智能体在记忆中自发涌现时空因果结构
Spacetime Emergence in the Memory of a Learning Agent
物理学家训练了个强化学习智能体，没告诉它时空规则，它自己学出了Minkowski时空的因果结构，思路很妙。
一篇 arXiv 论文训练了一个 model-based 强化学习智能体，任务是最大化与量子场相互作用的局域量子探针之间的量子互信息，训练中不提供任何时空度规或因果结构信息。智能体为完成任务构建的内部预测模型中，其 planner 发展出闵可夫斯基时空特有的零结构（null structure）。研究者据此高精度重构了 Minkowski 度规的因果结构，说明时空几何可以从智能体成功的预测与行动中推导出来。这是展示时空概念从操作性量子经验中涌现的第一步。
Spacetime Emergence in the Memory of a Learning Agent
We show that the causal structure of spacetime can emerge within the memory of a learning agent performing a quantum information task. We train a model-based reinforcement-learning agent to maximize the quantum mutual information between localized quantum probes interacting with a quantum field in Minkowski spacetime, without directly providing it with information regarding the spacetime metric or causal structure. In learning to accomplish this task, the reinforcement-learning agent constructs an internal predictive model whose planner develops the characteristic null structure of spacetime, allowing us to reconstruct the causal structure of the Minkowski metric with high accuracy. Within this task, spacetime geometry is obtained from an agent's successful predictions and actions, providing a first step toward showing that spacetime concepts emerge from operational quantum experience.