In the Newcomb problem, the standard arguments for taking either one box or both boxes adduce what seem to be relevant considerations, but they are not complete arguments, and attempts to complete the arguments rely upon incorrect principles of rational decision making. It is argued that by considering how the predictor is making his prediction, we can generate a more complete argument, and this in turn supports a form of causal decision theory.

I develop and defend a version of what I call Disposition-Based Decision Theory (or DBDT). I point out important problems in David Gauthier’s (1985, 1986) formulation of DBDT, and carefully develop a more defensible formulation. I then compare my version of DBDT to the currently most widely accepted decision theory, Causal Decision Theory (CDT). Traditional intuition-based arguments fail to give us any strong reason to prefer either theory over the other, but I propose an alternative strategy for resolving this debate. (...) I argue that we should embrace DBDT because it does better than CDT at the work that we, as a matter of empirical fact, commonly call upon a notion of rationality to do. (shrink)

A transformative decision rule transforms a given decision probleminto another by altering the structure of the initial problem,either by changing the framing or by modifying the probability orvalue assignments. Examples of decision rules belonging to thisclass are the principle of insufficient reason, Isaac Levi'scondition of E-admissibility, the de minimis rule, andthe precautionary principle. In this paper some foundationalissues concerning transformative decision rules are investigated,and a couple of formal properties of this class of rules areproved.