Reasonably Rational: Reasoning about Reasons Behind Preferences Using Modal Logic

Abstract

Reasoning about preferences is a fundamental component of rationality, and therefore central in AI and computational social choice. Most logic-based frameworks for representing and reasoning about preferences assume that preferences are arbitrarily given, typically as a ranking of a set of alternatives or using utilities, with little concern about how preferences are formed or where they come from. Recent work in rational choice theory, however, has devoted attention to giving more internal structure to the notion of rationality, focusing more on the faculties of individual agents, such as their mood, mindset, and motivating reasons. In this paper we develop a modal logic for reasoning about preferences that depend on a set of motivationally salient properties, based on recent work on reasons behind preferences by Dietrich and List. The main result is that we show how the problem of reasoning in this logic can be translated to reasoning in a standard modal logic (KT with universal modality), and consequently that reasoning systems and algorithms developed for modal logic (with universal modality) can be employed for reasoning about reason-based preferences.