How do people think about Constraint Problems?

A paper on our work about how people think about constraint programming has just been published in anticipation of the prestigious Conference on Principles and Practice of Constraint Programming (CP 2022). The paper is accessible through this address.

The work takes place at the intersection of Human-Computer Interaction and Constraint Programming.

We analyzed how non-experts tried to solve constrained programming problems.

Image showing a few examples of how people solved common constraint programming problems, such as scheduling.

This is work with Ruth Hoffmann, Xu Zhu, and Özgür Akgün, from the School of Computer Science at the University of St Andrews (my previous main institution).

This follows our previous work on how people visually represent discrete contraint problems (at the IEEE Transations on Visualization and Computer Graphics).

Dr Hoffmann has also presented at ModRef a synthesis on both pieces of work.

Finally, the SACHI group posted a blog post with a bit more information.

St Andrews + UVic PhD Scholarship on Machine Learning and Visualization

We are advertising a unique cross-continental opportunity to carry out cutting-edge research on Machine Learning and Information Visualization across two continents at two leading institutions, the University of St Andrews (Scotland) and the University of Victoria (Canada).

For administrative details, conditions and an initial description of the research see: the official Scholarship Announcement.

Supervision is collaborative between Dr Juan Ye and Uta Hinrichs (St Andrews) and myself (Miguel Nacenta–University of Victoria). Applications are accepted until June 30th, 2020. Feel free to drop me a line at nacenta at uvic dot ca if you want to discuss your application informally with me.