  As being widely used to measure human intelligence, Raven's Progressive
Matrices (RPM) tests also pose a great challenge for AI systems. There is a
long line of computational models for solving RPM, starting from 1960s, either
to understand the involved cognitive processes or solely for problem-solving
purposes. Due to the dramatic paradigm shifts in AI researches, especially the
advent of deep learning models in the last decade, the computational studies on
RPM have also changed a lot. Therefore, now is a good time to look back at this
long line of research. As the title -- ``a comprehensive introduction'' --
indicates, this paper provides an all-in-one presentation of computational
models for solving RPM, including the history of RPM, intelligence testing
theories behind RPM, item design and automatic item generation of RPM-like
tasks, a conceptual chronicle of computational models for solving RPM, which
reveals the philosophy behind the technology evolution of these models, and
suggestions for transferring human intelligence testing and AI testing.

Artificial Intelligence