A Fuzzy Classifier System That Generates Linguistic Rules for Pattern Classification Problems
Selected papers from the EEE/Nagoya-University World Wisepersons Workshop on Fuzzy Logic, Neural Networks, and Evolutionary Computation
Pareto-Front Exploration with Uncertain Objectives
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Decision making under uncertainty using imprecise probabilities
International Journal of Approximate Reasoning
Higher order models for fuzzy random variables
Fuzzy Sets and Systems
Fuzzy classifier identification using decision tree and multiobjective evolutionary algorithms
International Journal of Approximate Reasoning
Valued Hesitation in Intervals Comparison
SUM '07 Proceedings of the 1st international conference on Scalable Uncertainty Management
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
A Unified Model for Multilabel Classification and Ranking
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Genetic learning of fuzzy rules based on low quality data
Fuzzy Sets and Systems
International Journal of Approximate Reasoning
Multi-objective optimization of problems with epistemic uncertainty
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Artificial Intelligence in Medicine
A fuzzy cognitive map approach to differential diagnosis of specific language impairment
Artificial Intelligence in Medicine
Rule Weight Specification in Fuzzy Rule-Based Classification Systems
IEEE Transactions on Fuzzy Systems
Advocating the Use of Imprecisely Observed Data in Genetic Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Upper and lower probabilities induced by a fuzzy random variable
Fuzzy Sets and Systems
Upper and lower probabilities induced by a fuzzy random variable
Fuzzy Sets and Systems
Mark-recapture techniques in statistical tests for imprecise data
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
Expert Systems with Applications: An International Journal
Inner and outer fuzzy approximations of confidence intervals
Fuzzy Sets and Systems
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For diagnosing dyslexia in early childhood, children have to solve non-writing based graphical tests. Human experts score these tests, and decide whether the children require further consideration on the basis of their marks. Applying artificial intelligence techniques for automating this scoring is a complex task with multiple sources of uncertainty. On the one hand, there are conflicts, as different experts can assign different scores to the same set of answers. On the other hand, sometimes the experts are not completely confident with their decisions and doubt between different scores. The problem is aggravated because certain symptoms are compatible with more than one disorder. In case of doubt, the experts assign an interval-valued score to the test and ask for further information about the child before diagnosing him. Having said that, exploiting the information in uncertain datasets has been recently acknowledged as a new challenge in genetic fuzzy systems. In this paper we propose using a genetic cooperative-competitive algorithm for designing a linguistically understandable, rule-based classifier that can tackle this problem. This algorithm is part of a web-based, automated pre-screening application that can be used by the parents for detecting those symptoms that advise taking the children to a psychologist for an individual examination.