  Raven's Progressive Matrices is a family of classical intelligence tests that
have been widely used in both research and clinical settings. There have been
many exciting efforts in AI communities to computationally model various
aspects of problem solving such figural analogical reasoning problems. In this
paper, we present a series of computational models for solving Raven's
Progressive Matrices using analogies and image transformations. We run our
models following three different strategies usually adopted by human testees.
These models are tested on the standard version of Raven's Progressive
Matrices, in which we can solve 57 out 60 problems in it. Therefore, analogy
and image transformation are proved to be effective in solving RPM problems.
