@inproceedings{9d767fa8631147e29ff4a4cf549e338e,
title = "Intelligent decision-making approach based on fuzzy-causal knowledge and reasoning",
abstract = "Our intelligent decision-making approach (IDMA) is an instance of cognitive computing. It applies causality as common sense reasoning and fuzzy logic as a representation for qualitative knowledge. Our IDMA collects raw knowledge of humans through psychological models to tailor a knowledge-base (KB). The KB manages different repositories (e.g., cognitive maps (CM) and an ontology) to depict the object of study. The IDMA traces fuzzy-causal inferences to simulate causal behavior and estimate causal outcomes for decision-making. In order to test our approach, it is linked to the sequencing module of an intelligent and adaptive web-based educational system (IAWBES). It is used to provide student-centered education and enhance the students' learning by intelligent and adaptive functionalities. The results reveal users of an experimental group reached 17% of better learning than their peers of the control group.",
keywords = "Fuzzy-causal reasoning, cognitive map, content model, decision-making, knowledge-base, ontology, psychological models, student model",
author = "Alejandro Pe{\~n}a-Ayala and Riichiro Mizoguchi",
year = "2012",
doi = "10.1007/978-3-642-31087-4_55",
language = "Ingl{\'e}s",
isbn = "9783642310867",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "534--543",
booktitle = "Advanced Research in Applied Artificial Intelligence - 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, Proceedings",
note = "25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012 ; Conference date: 09-06-2012 Through 12-06-2012",
}