A qualitative reasoning approach for measuring citizens' satisfaction

This paper lies within the domain of learning algorithms based on fuzzy logic connectives. It is shown how the use of qualitative information in a learning process will increase the power of generalization. A software tool able to work simultaneously with qualitative and quantitative data is constructed over the discrete structure of absolute orders of magnitude spaces. The software developed will provide city hall councillors with useful information recovered from the data they have collected in a survey designed to evaluate sustainability. The use of LAMDA algorithm to measure the satisfaction of citizens in the patterns is presented.