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S. Hélie, “Modélisation de L'apprentissage Ascendant des Connaissances Explicites dans une Architecture Cognitive Hybride,” PHD, DIC, UQAM, Montréal, 2007.

has been cited by the following article:

• TITLE: Identifying Causes Helps a Tutoring System to Better Adapt to Learners during Training Sessions

  AUTHORS: Usef Faghihi, Philippe Fournier-Viger, Roger Nkambou, Pierre Poirier

  KEYWORDS: Cognitive Agents, Computational Causal Modeling and Learning, Emotions

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.3 No.3, August 5, 2011

  ABSTRACT: This paper describes a computational model for the implementation of causal learning in cognitive agents. The Conscious Emotional Learning Tutoring System (CELTS) is able to provide dynamic fine-tuned assistance to users. The integration of a Causal Learning mechanism within CELTS allows CELTS to first establish, through a mix of datamining algorithms, gross user group models. CELTS then uses these models to find the cause of users' mistakes, evaluate their performance, predict their future behavior, and, through a pedagogical knowledge mechanism, decide which tutoring intervention fits best.