An approach to enhance argument-based multi-criteria decision systems with conditional preferences and explainable answers

Abstract

In our current society, it is very common to have access to a huge amount of information and scenarios in which it is possible to choose among a great number of alternatives. Therefore, systems that automate or assist with the decision-making process are becoming crucial. Those systems should allow users to represent their preferences accurately, even in scenarios where the user has many forms of comparing the available alternatives. In this paper, we propose an argument-based framework for multi-criteria decision-making based on conditional rules, that allows users to encode their preferences among the comparison criteria in terms of requirement and tolerance values. From these rules, arguments that are involved in the comparison process are generated. In order to comply with users’ demands for explanations of the given answers, our proposed framework can provide qualitative explanations about the argumentation process, and also an explanatory graph that shows how all the alternatives were ranked and the connections with the user’s rules that were used. We also show the results of an empirical analysis of the performance of a developed prototype.