论文标题
并行光子加速器，用于使用光时空混乱进行决策
Parallel photonic accelerator for decision making using optical spatiotemporal chaos
论文作者
论文摘要
光子加速器引起了人工智能应用中越来越多的关注。多武器的强盗问题是使用强化学习决策的基本问题。但是，由于物理实现的技术困难，在实验中尚未证明光子决策的可伸缩性。我们提出了一个平行的光子决策系统，用于使用光时空混乱来解决大规模的多臂匪徒问题。我们在线解决了一个512臂的强盗问题，该问题比以前的实验大得多。正确决策的缩放属性是根据插槽计算机数量的函数进行检查的，该数量为0.86的指数。该指数小于以前的工作，表明所提出的平行原理的优越性。这项实验演示促进了光子决策，以解决将来光子加速器的大规模多臂匪徒问题。
Photonic accelerators have attracted increasing attention in artificial intelligence applications. The multi-armed bandit problem is a fundamental problem of decision making using reinforcement learning. However, the scalability of photonic decision making has not yet been demonstrated in experiments, owing to technical difficulties in physical realization. We propose a parallel photonic decision-making system for solving large-scale multi-armed bandit problems using optical spatiotemporal chaos. We solve a 512-armed bandit problem online, which is much larger than previous experiments by two orders of magnitude. The scaling property for correct decision making is examined as a function of the number of slot machines, evaluated as an exponent of 0.86. This exponent is smaller than that in previous work, indicating the superiority of the proposed parallel principle. This experimental demonstration facilitates photonic decision making to solve large-scale multi-armed bandit problems for future photonic accelerators.
