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Quantum Speedup for Active Learning Agents

机译:主动学习代理的量子加速

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Can quantum mechanics help us build intelligent learning agents? A defining signature of intelligent behavior is the capacity to learn from experience. However, a major bottleneck for agents to learn in real-life situations is the size and complexity of the corresponding task environment. Even in a moderately realistic environment, it may simply take too long to rationally respond to a given situation. If the environment is impatient, allowing only a certain time for a response, an agent may then be unable to cope with the situation and to learn at all. Here, we show that quantum physics can help and provide a quadratic speedup for active learning as a genuine problem of artificial intelligence. This result will be particularly relevant for applications involving complex task environments.
机译:量子力学可以帮助我们建立智能学习代理吗?智能行为的定义标志是从经验中学习的能力。但是,代理在现实生活中学习的主要瓶颈是相应任务环境的规模和复杂性。即使在适度现实的环境中,合理地响应给定情况也可能花费太长时间。如果环境不耐烦,仅允许一定时间做出响应,那么座席可能无法应对这种情况并根本无法学习。在这里,我们证明了量子物理学可以帮助主动学习作为人工智能的真正问题,并为二次学习提供二次加速。对于涉及复杂任务环境的应用程序,此结果将特别重要。

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