We describe initial experiments on human norm representations in which the context specificity of norms features prominently. We then provide a formal representation of norms and a machine learning algorithm to learn norms under uncertainty from these human data, while preserving their context specificity.
@inproceedings{sarathyetal2017cogsci, title={Mental Representations and Computational Modeling of Context-Specific Human Norm Systems}, author={Vasanth Sarathy and Matthias Scheutz and Joseph Austerweil and Yoed Kenett and Mowafak Allaham and Bertram Malle}, year={2017}, booktitle={Proceedings of the 39th Annual Meeting of the Cognitive Science Society}, url={https://hrilab.tufts.edu/publications/sarathyetal2017cogsci.pdf} }