@inproceedings{541c6512cbee4c5b9611b839dc2b5fbf,
title = "Producer/Consumer Problems",
abstract = "Interactive constraint systems often suffer from infeasibility (no solution) due to conflicting user constraints. A common approach to recover feasibility is to eliminate the constraints that cause the conflicts in the system. This approach allows the system to provide an explanation as: 'if the user is willing to drop some of their constraints, there exists a solution'. However, this form of explanation might not be very informative. A counter-factual explanation is a type of explanation that can provide a basis for the user to recover feasibility by helping them understand what changes can be applied to their existing constraints rather than removing them. We propose an efficient approach NoPropCounter-factualXplain to find counter-factual explanations for infeasible problems. We also propose a version of this algorithm which takes into account preferences called PrefnoPropCounter-factualXplain. We showcase it's usability in real world scenario using the producer/consumer constraint which is useful in problems which involve resource allocation.",
keywords = "counter-factual explanation, maximal explanation, minimal exclusion set",
author = "Gupta, \{Sharmi Dev\} and Helmut Simonis and Luis Quesada and Barry O'Sullivan",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 37th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2025 ; Conference date: 03-11-2025 Through 05-11-2025",
year = "2025",
doi = "10.1109/ICTAI66417.2025.00054",
language = "English",
series = "Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI",
publisher = "IEEE Computer Society",
pages = "363--370",
booktitle = "Proceedings - 2025 IEEE 37th International Conference on Tools with Artificial Intelligence, ICTAI 2025",
address = "United States",
}