Publication Topics constraint handling,constraint satisfaction problems,decision support systems,multi-agent systems,optimisation,Internet,
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Abstract. Beliefs, preferences and constraints occur together in many real world problems. However, reasoning with such intertwinement is rather unexplored in the AI literature. In this paper, we introduce a model whereby agents seek for decisions that satisfy their preferences based on their beliefs subject to certain constraints by extending.
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Né à Djerba Tunisie.Titulaire d'un master professionnel en ingénierie financière de l'ISG de Gabès (2011) et maîtrise en gestion des institutions financières de l'ESC de Tunis (2008).
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DOI: 10.18293/SEKE2018-133 Corpus ID: 53241619; Belief Function Theory in Constraint Satisfaction Problems: a Unifying Approach @inproceedings{Rouahi2018BeliefFT, title={Belief Function Theory in Constraint Satisfaction Problems: a Unifying Approach}, author={Aouatef Rouahi and Kais Ben Salah and Khaled Gh{\'e}dira}, booktitle={International Conference on Software Engineering and Knowledge.
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Kais Ben Salah Khaled Ghedira Rania Abdelhedi Najla Kharrat Year: 2021 A Proposal of Clinical Decision Support System Using Ensemble Learning for Coronary Artery Disease Diagnosis MOBIHEALTH Springer DOI: 10.1007/978-3-030-70569-5_19.
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College of Computer Science and Engineering, University of Jeddah, Jeddah - Cited by 16 - Multi-Agent Systems
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Aouatef Rouahi, Kais Ben Salah, K. Ghédira; Published 2013; Computer Science; TLDR. A new CSP extension is introduced, labeled Belief Constraint Satisfaction Problem (BCSP), fulfilling two tasks that are managing imperfection and modeling flexibility, and merging the belief function theory and the CSP formalism.
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Kais Ben Salah's research while affiliated with Institut Supérieur de Gestion de Tunis and other places Overview What is this page? This page lists the scientific contributions of an author,.
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Rawia Sammout, Kais Ben Salah, Khaled Ghédira, Rania Abdelhedi, Najla Kharrat: A Proposal of Clinical Decision Support System Using Ensemble Learning for Coronary Artery Disease Diagnosis. MobiHealth 2020: 300-314
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