Towards Replication in Computational Cognitive Modeling: A Machine Learning Perspective

Chris Emmery*, Ákos Kádár, Travis J Wiltshire, Andrew T Hendrickson

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


The suggestions proposed by Lee et al. to improve cognitive modeling practices have significant parallels to the current best practices for improving reproducibility in the field of Machine Learning. In the current commentary on `Robust modeling in cognitive science', we highlight the practices that overlap and discuss how similar proposals have produced novel ongoing challenges, including cultural change towards open science, the scalability and interpretability of required practices, and the downstream effects of having robust practices that are fully transparent. Through this, we hope to inform future practices in computational modeling work with a broader scope.
Original languageEnglish
Pages (from-to)242-246
JournalComputational Brain & Behavior
Early online date31 Jul 2019
Publication statusPublished - 31 Jul 2019


  • Reproducibility
  • Machine Learning
  • Cogntive modeling
  • Cognitive psychology


Dive into the research topics of 'Towards Replication in Computational Cognitive Modeling: A Machine Learning Perspective'. Together they form a unique fingerprint.

Cite this