  The framework of algorithmic knowledge assumes that agents use deterministic
knowledge algorithms to compute the facts they explicitly know. We extend the
framework to allow for randomized knowledge algorithms. We then characterize
the information provided by a randomized knowledge algorithm when its answers
have some probability of being incorrect. We formalize this information in
terms of evidence; a randomized knowledge algorithm returning ``Yes'' to a
query about a fact \phi provides evidence for \phi being true. Finally, we
discuss the extent to which this evidence can be used as a basis for decisions.
