Conversational Modeling for Constraint Satisfaction

Authors

  • Eugene C. Freuder Insight Centre for Data Analytics, University College Cork, Cork, Ireland

DOI:

https://doi.org/10.1609/aaai.v38i20.30268

Keywords:

CSO: Constraint Learning And Acquisition, CSO: Constraint Programming, HAI: Human-Computer Interaction, HAI: Human-in-the-loop Machine Learning, NLP: Conversational AI/Dialog Systems, NLP: (Large) Language Models

Abstract

Many problems, from Sudoku to factory scheduling, can be regarded as constraint satisfaction problems. A key component of real world problem solving is a conversation between a constraint programming expert and a problem domain expert to specify the problem to be solved. This presentation argues that the time is ripe for progress in automating the constraint programmer side of this conversation and suggests promising avenues for this pursuit.
AAAI-24 / IAAI-24 / EAAI-24 Proceedings Cover

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Published

2024-03-24

How to Cite

Freuder, E. C. (2024). Conversational Modeling for Constraint Satisfaction. Proceedings of the AAAI Conference on Artificial Intelligence, 38(20), 22592-22597. https://doi.org/10.1609/aaai.v38i20.30268

Issue

Vol. 38 No. 20: AAAI-24 Special Track AI for Social Impact, Senior Member Presentations, New Faculty Highlights, Journal Track

Section

Senior Member Presentation: Blue Sky Papers