An approach to generalizing the handling of preferences in argumentation-based decision-making systems

Abstract

As a practical mechanism for formalizing commonsense reasoning, argumentation has shown its potential for applications in diverse areas, many related to decision-making in knowledge-based systems. Following this line, and for helping users in making a better and informed decision, different recommender systems proposals have been developed in the argumentation literature. We will use recommender systems as a good example where to exercise our proposal. In particular, the role of preference criterion in argumentation-based recommender systems which is used to compare competing arguments is central to the user’s query answering process where if the criterion does not adjust to the represented domain, the system could fail by being undecided too often. Therefore, having tools that allow to select and change the argument comparison mechanism has to be used become a central issue. Argumentation-based recommender systems that offer these tools provide an interesting ability that can be used for improving the reasoning capabilities in this type of systems. This work introduces an approach to handle multiple argument preference criteria in argumentation-based recommender systems and general knowledge-based decision support systems. More precisely, the proposal allows changing the information that a criterion can use in the argument comparison process and specify how several criteria can be simultaneously used in such process as well; to achieve that goal, a set of operators to combine several criteria is presented. The knowledge representation and reasoning is performed in Defeasible Logic Programming, a defeasible argumentation formalism based on logic programming.