Modeling influence in multi-agent preference aggregation over combinatorial domains

We consider multi-agent settings where a set of agents want to take a collective decision, based on their preferences over the possible candidate options. While agents have their initial inclination, they may interact and influence each other, and therefore modify their preferences, until hopefully they reach a stable state and declare their final inclination. At that point, a voting rule is used to aggregate the agents’ preferences and generate the collective decision. Recent work has modeled the influence phenomenon in the case of voting over a single issue. Here we generalize this model to account for preferences over combinatorially structured domains including several issues. We propose a way to model influence and to aggregate preferences, by interleaving voting and influence convergence, when agents express their preferences as CPnets. We also provide results about the resistance of this setting to bribery and manipulation.