A Dynamic Rationalization of Distance Rationalizability

Distance rationalizability is an intuitive paradigm for developing and studying voting rules: given a notion of consensus distance function on preference profiles, rationalizable rule selects alternative that closest to being winner. Despite its appeal, faces the challenge connecting chosen measure operational social desirability. We tackle this issue via decision-theoretic framework dynamic choice, in which choice Markov decision process (MDP) models dynamics voter preferences response winner selection. show that, prominent class functions, one can construct MDP, with natural rewards, such (votewise) respect unanimity iff it (deterministic) optimal policy MDP. This provides rationale rationalizability, demonstrating equivalence rules static sense selection maximize societal utility process.