Central to the success of adaptive systems is their ability to interpret signals from their environment and respond accordingly -- they act as agents interacting with their surroundings. Such agents typically perform better when able to execute increasingly complex strategies. This comes with a cost: the more information the agent must recall from its past experiences, the more memory it will need. Here we investigate the power of agents capable of quantum information processing. We uncover the most general form a quantum agent need adopt to maximise memory compression advantages, and provide a systematic means of encoding their memory states. We show these encodings can exhibit extremely favourable scaling advantages relative to memory-minimal classical agents, particularly when information must be retained about events increasingly far into the past.
翻译:适应系统成功的关键在于能够解释来自环境的信号并做出相应的反应 -- -- 它们充当与周围环境互动的代理人。这些代理人通常在能够执行日益复杂的战略时表现更好。这需要成本:代理人必须从过去的经验中记住的信息越多,它就越需要记忆。我们在这里调查能够处理量子信息的代理人的力量。我们发现量子代理人需要采用的最一般的形式来最大限度地发挥记忆压缩优势,并提供系统化的编码手段来编码它们的记忆状态。我们显示这些编码在与记忆-最小的古典代理人相比,能够显示出非常有利的规模优势,特别是在必须保存关于日益深入历史的事件的信息的时候。