MODELANDO LA TOMA DE DECISIONES MEDIANTE FUSIÓN DE CREENCIAS

Belief merging is a relatively recent technique with the aim of combining pieces of infor- mation, possibly inconsistent, coming from different sources. This process is done by a merging operator, in the literature we found mainly the theoretical basis of operators. However, this technique is still little known and there is scarce evidence about its applicability to solve real-world problems. In this paper we propose to use belief merging in order to solve everyday decision-making problems, in which participants with the same level have contradictory opinions, by “merging” these opinions and generating a common non-contradictory opinion representing the views of the majority. We describe in detail three belief merging operators with differing properties: ∆Σ, ∆GMax , y ∆ps (PS-Merge); afterwards, the classic belief merging examples are presented in natural language as decision-making practical scenarios; finally, we present an online open source Belief Merging Prototype to support on diverse decision-making processes