New trends in information aggregation

Information aggregation is one of the key issues in the development of intelligent systems, like neural networks, neuro-fuzzy systems, fuzzy knowledge based systems, vision and decision making systems, etc. Fuzzy set theory provides a host of attractive aggregation operators for integrating the membership values representing uncertain information. The variety of these operators might be confusing and make it difficult to decide which one to use in a specific model or situation. The tutorial gives a survey of the existing aggregation connectives starting from the classical Zadehian-operators, through the theory of t-operators, till the most up-to-date operators, containing the results of the author and his colleagues on entropy and evolutionary operators.