Zeev Goldschmidt

Several philosophers have proposed Knowledge-Based Decision Theories (KDTs)—theories that require agents to maximize expected utility as yielded by utility and probability functions that depend on the agent’s knowledge. Proponents of KDTs argue that such theories are motivated by Knowledge-Reasons norms that require agents to act only on reasons that they know. However, no formal derivation of KDTs from Knowledge-Reasons norms has been suggested, and it is not clear how such norms justify the particular ways in which KDTs relate knowledge and rational action. In this paper, I suggest a new axiomatic method for justifying KDTs and providing them with stronger normative foundations. I argue that such theories may be derived from constraints on the relation between knowledge and preference, and that these constraints may be evaluated relative to intuitions regarding practical reasoning. To demonstrate this, I offer a representation theorem for a KDT proposed by Hawthorne and Stanley (2008) and briefly evaluate it through its underlying axioms. In section 1, I present knowledge-based decision theories generally and the versions of such theories suggested in the literature. In section 2, I argue that KDTs and theories of practical reasoning conjoined with Knowledge-Reasons norms generate constraints on the same relation—the relation between knowledge and preference. In section 3, I present a formal framework in which constraints on this relation may be expressed and from which KDTs may be derived. In section 4, I present a representation theorem for a specific KDT. In section 5, I briefly evaluate the axioms of the theory, and in section 6, I conclude.

We study the representation of attitudes to risk in Jeffrey’s decision-theoretic framework suggested by Stefánsson and Bradley :602–625, 2015; Br J Philos Sci 70:77–102, 2017) and Bradley :231–248, 2016; Decisions theory with a human face, Cambridge University Press, Cambridge, 2017). We show that on this representation, the value of any prospect may be expressed as a sum of two components, the prospect’s instrumental value and the prospect’s intrinsic value. Both components have an expectational form. We also make a distinction between a prospect’s overall intrinsic value and a prospect’s conditional intrinsic value given each one of its possible outcomes and argue that this distinction has great explanatory power. We explore the relation between these two types of intrinsic values and show that they are determined at the level of preferences. Finally, we explore the relation between the intrinsic values of different prospects and point to a strong restriction on this relation that is implicit in Jeffrey’s axioms. We suggest a natural interpretation to this restriction.