Monte Carlo Complexity of Global Solution of Integral Equations

The problem of global solution of Fredholm integral equations is studied. This means that one seeks to approximate the full solution function (as opposed to the local problem, where only the value of the solution in a single point or a functional of the solution is sought). The Monte Carlo complexity is analyzed, i. e. the complexity of stochastic solution of this problem. The framework for this analysis is provided by informationbased complexity theory. The investigations complement previous ones on stochastic complexity of local solution and on deterministic complexity of both local and global solution. The results show that even in the global case Monte Carlo algorithms can perform better than deterministic ones, although the difference is not as large as in the local case.