Pareto Optimality and Strategy Proofness in Group Argument Evaluation (Extended Version)
This work addresses the problem of ensuring social optimality and strategic immunity in group argument evaluation for agents with preferences, but it is incremental as it builds on prior operators.
The paper analyzes three existing argument-based aggregation operators for collective argument evaluation, examining their Pareto optimality and strategy proofness under various agent preference classes, and highlights trade-offs between strategic manipulability, social optimality, and logical criteria.
An inconsistent knowledge base can be abstracted as a set of arguments and a defeat relation among them. There can be more than one consistent way to evaluate such an argumentation graph. Collective argument evaluation is the problem of aggregating the opinions of multiple agents on how a given set of arguments should be evaluated. It is crucial not only to ensure that the outcome is logically consistent, but also satisfies measures of social optimality and immunity to strategic manipulation. This is because agents have their individual preferences about what the outcome ought to be. In the current paper, we analyze three previously introduced argument-based aggregation operators with respect to Pareto optimality and strategy proofness under different general classes of agent preferences. We highlight fundamental trade-offs between strategic manipulability and social optimality on one hand, and classical logical criteria on the other. Our results motivate further investigation into the relationship between social choice and argumentation theory. The results are also relevant for choosing an appropriate aggregation operator given the criteria that are considered more important, as well as the nature of agents' preferences.