APPROXIMATE REASONING TECHNIQUES

Content:

In this course, several methods and techniques to represent, reason and fusion of incomplete or uncertain information are surveyed. Main topics will be: uncertainty measures, probabilistic reasoning (Bayesian networks), evidential reasoning (Dempster-Shafer), possibilistic logic and fuzzy systems, aggregation measures, multicriteria decision models, decision under uncertainty. Introduction of the foundations of classification systems and more specially on those techniques based on fuzzy sets. A deep study of the similarity functions is made to use in Classification and Similarity Reasoning.

Uncertainty Measures
Bayesian Networks
Evidencial Reasoning
Fuzzy Systems
Information Fusion
Models for Multicriteria Decision
Classification Techniques
Similarity Reasoning.

Advisors

Bibliography

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