"Reason-based rationalizations" explain an agent's choices by specifying which properties of the options or choice context he/she cares about (the "motivationally salient properties") and how he/she cares about these properties the "fundamental preference relation"). We characterize the...

According to standard rational choice theory, as commonly used in political science and economics, an agent's fundamental preferences are exogenously fixed, and any preference change over decision options is due to Bayesian information learning. Although elegant and parsimonious, such a model...

The widely discussed `discursive dilemma' shows that majority voting in a group of individuals on logically connected propositions may produce irrational collective judgments. We generalize majority voting by considering quota rules, which accept each proposition if and only if the number of...

Behaviourism is the view that preferences, beliefs, and other mental states in social-scienti�c theories are auxiliary constructs re-describing people's behav- ioural dispositions. Mentalism is the view that they capture real phenomena, no less existent than the unobservable entities and...

We introduce a “reason-based” way of rationalizing an agent’s choice behaviour, which explains choices by specifying which properties of the options or choice context the agent cares about (the “motivationally salient properties”) and how he or she cares about these properties (the...

In the theory of judgment aggregation, it is known for which agendas of propositions it is possible to aggregate individual judgments into collective ones in accordance with the Arrow-inspired requirements of universal domain, collective rationality, unanimity preservation, non-dictatorship and...

How can different individuals' probability assignments to some events be aggregated into a collective probability assignment? Classic results on this problem assume that the set of relevant events -- the agenda -- is a σ-algebra and is thus closed under disjunction (union) and conjunction...

This paper characterizes different belief revision rules in a unified framework: Bayesian revision upon learning some event, Jeffrey revision upon learning new probabilities of some events, Adams revision upon learning some new conditional probabilities, and `dual-Jeffrey' revision upon learning...

What is the relationship between degrees of belief and (all-or-nothing) beliefs? Can the latter be expressed as a function of the former, without running into paradoxes? We reassess this “belief-binarization” problem from the perspective of judgmentaggregation theory. Although some...

How can different individuals' probability functions on a given σ-algebra of events be aggregated into a collective probability function? Classic approaches to this problem often require `event-wise independence': the collective probability for each event should depend only on the individuals'...