Abstract

Background Artificial intelligence, like any science, must rely on reproducible experiments to validate results. Objective To give practical and pragmatic recommendations for how to document AI research so that results are reproducible. Method Our analysis of the literature shows that AI publications currently fall short of providing enough documentation to facilitate reproducibility. Our suggested best practices are based on a framework for reproducibility and recommendations for best practices given by scientific organizations, scholars, and publishers. Results We have made a reproducibility checklist based on our investigation and described how every item in the checklist can be documented by authors and examined by reviewers. Conclusion We encourage authors and reviewers to use the suggested best practices and author checklist when considering submissions for AAAI publications and conferences.
Background

Objective

Method

Results

Conclusion

Date

2018

Authors

Odd Erik Gundersen, Yolanda Gil, David W Aha

Journal

AI Magazine

Volume

39

Issue

3