Time, hope, and independence: an argument for more structure in decision theory

My thesis explores alternatives to the orthodox model of decision theory. I criticise it by focusing on motivations that, for different reasons, I believe should not be labelled as a consequence. I start by describing what I call the orthodox theory of choice. I describe both the theories proposed by Von Neumann and Morgenstern (1944), and Savage (1954). This is followed by a discussion of the individuation strategy, and, in particular, John Broome’s proposal of an individuation by justifiers (Broome (1991)). I then focus on the Allais’s problem, and on how individuation can be employed to solve the problematic situation in which it puts orthodox decision theory. I argue against the practice of using this strategy as a general solution to cases such as the Allais’s problem. I then extend the concerns raised by the Allais’s problem to motivations that do not concern probabilities. I focus on dynamic decision making, and on a property of certain actions that arises from the passage of time: hope. This is interesting because it is no longer the probabilities that affect the decision maker, but an element that is not even represented in the standard model, namely time. I then describe the Kreps and Porteus’s model (Kreps and Porteus (1978)) for a preference for the timing of the resolution of uncertainty, where a preference for either early or late resolution of uncertainty is modelled explicitly. I show how making time an explicit part of the model allows one to model utility as depending on something other than consequences, while not violating dynamic consistency. I use the above case to claim that in some contexts - for example, if the decision maker is deciding for herself, and time is passing - it is preferable to model concerns that do not quite fit the label of a consequence explicitly, because the benefits of doing so surpass the costs. This seems to indicate that decision theory should be moving towards a pluralist approach, where different models are used depending on the decision context.