All models are wrong, some are useful, but are they reproducible? Commentary on Lee et al. (2019)

Lee et al. (2019) make several practical recommendations for replicable, useful cognitive modeling. They also point out that the ultimate test of the usefulness of a cognitive model is its ability to solve practical problems. In this commentary, we argue that for cognitive modeling to reach applied domains, there is a pressing need to improve the standards of transparency and reproducibility in cognitive modelling research. Solution-oriented modeling requires engaging practitioners who understand the relevant domain. We discuss mechanisms by which reproducible research can foster engagement with applied practitioners. Notably, reproducible materials provide a start point for practitioners to experiment with cognitive models and determine whether those models might be suitable for their domain of expertise. This is essential because solving complex problems requires exploring a range of modeling approaches, and there may not time to implement each possible approach from the ground up. We also note the broader benefits to reproducibility within the field.