This paper surveys recent developments on numerical algorithms for high dimensional multiple integration. First, we present Wozniakowski's theorem published in 1991, which revealed a remarkable connection between the integration error and the discrepancy via the classical Wiener measure. Then, we introduce low-discrepancy sequences, by means of which one can compute the arithmetic mean of a number of sample values of the integrand as an approximation to the integration. As a concrete construction method of low-discrepancy sequences, we give the definition of generalized Niederreiter sequences and a brief introduction of Niederreiter-Xing sequences, which are constructed by using algebraic function fields. Finally, we describe Smolyak's algorithm, which is an algorithm computing the weighted mean of sample values of the integrand. Sample points that this algorithm uses are called hyperbolic cross points. An interesting result by Wasilkowski and Wozniakowski on this algorithm is presented.