The de Finetti Theorem is a cornerstone of the Bayesian approach. Bernardo (1996) writes that its "message is very clear: if a sequence of observations is judged to be exchangeable, then any subset of them must be regarded as a random sample from some model, and there exists a prior distribution...

The paper considers an agent who must choose an action today under uncertainty about the consequence of any chosen action but without having in mind a complete list of all the contingencies that could influence outcomes. She conceives of some relevant (subjective) contingencies but she is aware...

The de Finetti Theorem is a cornerstone of the Bayesian approach. Bernardo (1996) writes that its "message is very clear: if a sequence of observations is judged to be exchangeable, then any subset of them must be regarded as a random sample from some model, and there exists a prior distribution...

The de Finetti Theorem on exchangeable predictive priors is generalized to a framework where preference is represented by Choquet expected utility with respect to a belief function (a special capacity). The resulting model provides behavioral foundations for the decision-maker's subjective...

The paper outlines an exchangeable non-Bayesian model of preference generalizing the Savage/de Finetti classic model of subjective expected utility preference with an exchangeable prior. The treatment is informal, and the emphasis is on motivation and potential applications rather than on...

The de Finetti Theorem is a cornerstone of the Bayesian approach. Bernardo (1996) writes that its "message is very clear: if a sequence of observations is judged to be exchangeable, then any subset of them must be regarded as a random sample from some model, and there exists a prior distribution...