Emilio Gamba, is a Ph.D. researcher in Constraint Programming and Machine Learning. His research focusses on integrating Explainbility in Constraint Solving to provide personalized/preferred explanations for Sudoku’s.
Bogaerts, B., Gamba, E., Guns, T., & Claes, J. (2020). Step-wise Explanations of Constraint Satisfaction Problems. In G. De Giacomo, A. Catala, B. Dilkina, M. Milano, S. Barro, A. Bugarin, & J. Lang (Eds.), ECAI 2020 - 24th European Conference on Artificial Intelligence, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Proceedings (Vol. 325, pp. 640-647). (Frontiers in Artificial Intelligence and Applications; Vol. 325). IOS Press. https://doi.org/10.3233/FAIA200149
Bogaerts, B., Gamba, E., & Guns, T. (2021). A Framework for Step-Wise Explaining How to Solve Constraint Satisfaction Problems. Artificial Intelligence, 300, 103550. https://doi.org/10.1016/j.artint.2021.103550
Gamba, E., Bogaerts, B., & Guns, T. (2021). Efficiently Explaining CSPs with Unsatisfiable Subset Optimization. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Published. https://doi.org/10.24963/ijcai.2021/191