  Multi-Agent Path Finding (MAPF) is an important core problem for many new and
emerging industrial applications. Many works appear on this topic each year,
and a large number of substantial advancements and performance improvements
have been reported. Yet measuring overall progress in MAPF is difficult: there
are many potential competitors, and the computational burden for comprehensive
experimentation is prohibitively large. Moreover, detailed data from past
experimentation is usually unavailable. In this work, we introduce a set of
methodological and visualisation tools which can help the community establish
clear indicators for state-of-the-art MAPF performance and which can facilitate
large-scale comparisons between MAPF solvers. Our objectives are to lower the
barrier of entry for new researchers and to further promote the study of MAPF,
since progress in the area and the main challenges are made much clearer.
