In this paper, a proposal for extending the fuzzy logic framework to researcher’s performance evaluation using the good properties of robustness and interpretability of compensatory fuzzy logic is presented. Results obtained with our model are more consistent with the way human make decisions. Additionally a case study to illustrate the applicability of the proposal is developed. Our main outcome is a new researcher’s evaluation based on compensatory fuzzy logic that gives results that are more robust and allows compensation. Moreover, this approach makes emphasis in using language in line with the computing with words paradigm.
Fuzzy cognitive maps have received increasing attention for the representation of causal knowledge, being especially useful in biomedicine. Recently some extension for using fuzzy cognitive maps using the paradigm of computing with words in order to provide causal models that are easily understood have been proposed. Nevertheless, there are situations in which experts hesitate between several values to assess the causal relation. To this end, we propose the use of of hesitant fuzzy linguistic term sets. Finally, the paper presents an illustrative example of the model for biomedical knowledge representation.
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