We study the worst case tractability of multivariate linear problems defined
on separable Hilbert spaces. Information about a problem instance consists of
noisy evaluations of arbitrary bounded linear functionals, where the noise is
either deterministic or random. The cost of a single evaluation depends on its
precision and is controlled by a cost function. We establish mutual
interactions between tractability of a problem with noisy information, the cost
function, and tractability of the same problem, but with exact information