Martin Peterson

Pragmatic arguments seek to demonstrate that you can be placed in a situation in which you will face a sure and foreseeable loss if you do not behave in accordance with some principle P. In this article I show that for every P entailed by the principle of maximizing expected utility you will not be better off from a pragmatic point of view if you accept P than if you don’t, because even if you obey the axioms of expected utility theory it is possible to place you in a situation in which you will face a certain and foreseeable loss. This shows that for a large class of Ps, there is no pragmatic difference between people who accept P and those who don’t.

abstract Even though much research has been devoted to studies of safety, the concept of safety is in itself under‐theorised, especially concerning its relation to epistemic uncertainty. In this paper we propose a conceptual analysis of safety. The paper explores the distinc‐tion between absolute and relative safety, as well as that between objective and subjective safety. Four potential dimensions of safety are discussed, viz. harm, probability, epistemic uncertainty, and control. The first three of these are used in the proposed definition of safety, whereas it is argued that control should not be included in a reasonable definition of safety. It is shown that strictly speaking, an objective safety concept is not attainable. Instead, an intersubjective concept is proposed that brings us as close as possible to an objective concept.

The concept of transformative decision rules provides auseful tool for analyzing what is often referred to as the`framing', or `problem specification', or `editing' phase ofdecision making. In the present study we analyze a fundamentalaspect of transformative decision rules, viz. permutability. A setof transformative decision rules is, roughly put, permutable justin case it does not matter in which order the rules are applied.It is argued that in order to be normatively reasonable, sets oftransformative decision rules have to satisfy a number ofstructural conditions that together imply permutability. Thisformal result gives support to a non-sequential theory of framing,i.e., a theory which prescribes no uniform order in which differentsteps in the framing process have to be performed.

This paper presents an axiomatization of the principle of maximizing expected utility that does not rely on the independence axiom or sure-thing principle. Perhaps more importantly the new axiomatization is based on an ex ante approach, instead of the standard ex post approach. An ex post approach utilizes the decision maker's preferences among risky acts for generating a utility and a probability function, whereas in the ex ante approach a set of preferences among potential outcomes are on the input side of the theory and the decision maker's preferences among risky acts on the output side

This up-to-date introduction to decision theory offers comprehensive and accessible discussions of decision-making under ignorance and risk, the foundations of utility theory, the debate over subjective and objective probability, Bayesianism, causal decision theory, game theory, and social choice theory. No mathematical skills are assumed, and all concepts and results are explained in non-technical and intuitive as well as more formal ways. There are over 100 exercises with solutions, and a glossary of key terms and concepts. An emphasis on foundational aspects of normative decision theory (rather than descriptive decision theory) makes the book particularly useful for philosophy students, but it will appeal to readers in a range of disciplines including economics, psychology, political science and computer science. • Has over 100 end of chapter review questions and exercises with solutions • Includes a chapter on how to draw a decision matrix • Explains the link between individual decision making, game theory and social choice theory Contents Preface; 1. Introduction; 2. The decision matrix; 3. Decisions under ignorance; 4. Decisions under risk; 5. Utility; 6. The mathematics of probability; 7. The philosophy of probability; 8. Why should we accept the preference axioms; 9. Causal vs. evidential decision theory; 10. Bayesian vs. non-Bayesian decision theory; 11. Game theory I: basic concepts and zero sum games; 12. Game theory II: nonzero sum and co-operative games; 13. Social choice theory; 14. Overview of descriptive decision theory; Appendix A. Glossary; Appendix B. Proof of the von Neumann-Morgenstern theorem; Further reading; Index.