Abstract
Classical decision theory does not provide a suitable theoretical basis for designing group decision agents because the concept of collective preference is not well defined. Here, we propose a model based on fuzzy preferences. A degree of truth is associated with the group preference relation. Fairness, equity, power of majority and compromise with significant minorities are modeled using concordance and discordance principles, reflecting the natural heuristic of collaborative groups making acceptable consensus decisions. Exploitation of the fuzzy group preference relation is performed solving a multiobjective optimization problem with an evolutionary algorithm. The designed agent shows very good performance in some test examples, obtaining better results than Condorcet and Borda methods.
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