论文标题
量子计算算法的温和介绍，并应用了通用预测
A Gentle Introduction to Quantum Computing Algorithms with Applications to Universal Prediction
论文作者
论文摘要
在这份技术报告中，我们为非物理学家提供了量子计算的基础介绍。在此引言中，我们详细描述了一些基础量子算法，包括：Deutsch-Jozsa算法，Shor's算法，杂货商搜索和计数算法的量子，并短暂地将Harrow-lloyd-Lloyd算法简要介绍。此外，我们对所罗门诺夫感应进行了介绍，这是一种预测的理论上最佳方法。然后，我们尝试使用量子计算来找到更好的算法来近似所罗诺夫诱导。这是通过使用其他量子计算算法的技术来完成计算先验速度的加速的技术，这是所罗门诺夫先验的近似，这是所罗门诺夫感应的关键部分。主要限制因素是计算的概率通常很小，以至于没有足够（通常很大）的试验，误差可能大于结果。如果可以通过量子计算来实现所罗诺夫感应近似值的实质性加速，则可以将其应用于智能代理领域，作为代理AIXI近似值的关键部分。
In this technical report we give an elementary introduction to Quantum Computing for non-physicists. In this introduction we describe in detail some of the foundational Quantum Algorithms including: the Deutsch-Jozsa Algorithm, Shor's Algorithm, Grocer Search, and Quantum Counting Algorithm and briefly the Harrow-Lloyd Algorithm. Additionally we give an introduction to Solomonoff Induction, a theoretically optimal method for prediction. We then attempt to use Quantum computing to find better algorithms for the approximation of Solomonoff Induction. This is done by using techniques from other Quantum computing algorithms to achieve a speedup in computing the speed prior, which is an approximation of Solomonoff's prior, a key part of Solomonoff Induction. The major limiting factors are that the probabilities being computed are often so small that without a sufficient (often large) amount of trials, the error may be larger than the result. If a substantial speedup in the computation of an approximation of Solomonoff Induction can be achieved through quantum computing, then this can be applied to the field of intelligent agents as a key part of an approximation of the agent AIXI.
