Debugging unsatisfiable constraint models can be a tedious task. Current tools allow a user
to extract a subset of constraints that render the problem unsatisfiable (MUS). However, in …

People want to rely on optimization algorithms for complex decisions but verifying the
optimality of the solutions can then become a valid concern, particularly for critical decisions …

Recent work suggests to explain trade-offs between soft goals in terms of their conflicts, ie,
minimal unsolvable soft-goal subsets. But this does not explain the conflicts themselves …

Given a user who asks why an algorithmic decision did not satisfy some conditions, a
counterfactual explanation takes the form of a minimally perturbed input that would have led …

Decision systems for solving real-world combinatorial problems must be able to report
infeasibility in such a way that users can understand the reasons behind it, and determine …

Real-world decision-making often involves working with many distinct objectives. However,
as we consider a larger number of objectives, performance degrades rapidly and many …

This thesis develops the first application of counterfactual explanations to optimal solutions
of discrete optimization problems. The techniques studied respond to a contrastive question …