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

    Abstract

    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
    Volume2
    Early online date31 Jul 2019
    DOIs
    Publication statusPublished - 31 Jul 2019

    Keywords

    • Reproducibility
    • Machine Learning
    • Cogntive modeling
    • Cognitive psychology

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