Non-Bayesian Decision Theory: Beliefs and Desires as Reasons for Action

ISBN-13: 9789048179572 / Angielski / Miękka / 2010 / 170 str.

Martin Peterson

Opis

For quite some time, philosophers, economists, and statisticians have endorsed a view on rational choice known as Bayesianism. The work on this book has grown out of a feeling that the Bayesian view has come to dominate the academic com- nitytosuchanextentthatalternative, non-Bayesianpositionsareseldomextensively researched. Needless to say, I think this is a pity. Non-Bayesian positions deserve to be examined with much greater care, and the present work is an attempt to defend what I believe to be a coherent and reasonably detailed non-Bayesian account of decision theory. The main thesis I defend can be summarised as follows. Rational agents m- imise subjective expected utility, but contrary to what is claimed by Bayesians, ut- ity and subjective probability should not be de?ned in terms of preferences over uncertain prospects. On the contrary, rational decision makers need only consider preferences over certain outcomes. It will be shown that utility and probability fu- tions derived in a non-Bayesian manner can be used for generating preferences over uncertain prospects, that support the principle of maximising subjective expected utility. To some extent, this non-Bayesian view gives an account of what modern - cision theory could have been like, had decision theorists not entered the Bayesian path discovered by Ramsey, de Finetti, Savage, and others. I will not discuss all previous non-Bayesian positions presented in the literature

Recenzje

From the reviews:

"This book presents an account of rational choice from a non-Bayesian point of view. ... this book argues that the non-Bayesian approach offers more action guidance to the decision maker. ... the book is well addressed to all researchers in the field of decision theory, and especially those with philosophical concerns." (Vangelis Grigoroudis, Zentralblatt MATH, Vol. 1151, 2009)

"Anyone concerned in the foundations of normative decision theory and who feels puzzled by the way this theory typically proceeds will doubtless welcome Martin Peterson's Non-Bayesian Decision Theory. ... Perterson's book is written in a clear and pleasant style, is well organized and shows an impressive mastery of both formal models and conceptual issues pertaining to contemporary decision theory. ... Its reading will be valuable to every scholar - philosopher or economist - interested by decision theory." (Mikaël Cozic, Economics and Philosophy, Vol. 27, 2011)

Spis treści

1. Introduction, 2.Bayesian decision theory, 3. Choosing what to decide, 4. Indeterminate preference, 5. Utility, 6. Probability, 7. Expected utility, 8. Risk aversion, 9. Appendix: Proofs

O autorze

Martin Peterson received his PhD in philosophy in 2003 from the Royal Institute of Technology, Stockholm. He is currently an associate professor of philosophy at Eindhoven University of Technology. Between 2005 and 2008 he worked for three years at the University of Cambridge, where he was a Research Fellow in the Department of History and Philosophy of Science and Director of Studies in Philosophy at St Edmund's College. He has also held teaching and research positions at the Royal Institute of Technology and at Lulea University of Technology.

Blurb

This book aims to present an account of rational choice from a non-Bayesian point of view. Rational agents maximize subjective expected utility, but contrary to what is claimed by Bayesians, the author argues that utility and subjective probability should not be defined in terms of preferences over uncertain prospects. To some extent, the author’s non-Bayesian view gives a modern account of what decision theory could have been like, had decision theorists not entered the Bayesian path discovered by Ramsey, Savage, and Jeffrey. The author argues that traditional Bayesian decision theory is unavailing from an action-guiding perspective. For the deliberating Bayesian agent, the output of decision theory is not a set of preferences over alternative acts - these preferences are on the contrary used as input to the theory. Instead, the output is a (set of) utility function(s) that can be used for describing the agent as an expected utility maximizer, which are of limited normative relevance.On the non-Bayesian view articulated by the author, utility and probability are defined in terms of preferences over certain outcomes. These utility and probability functions are then used for generating preferences over uncertain prospects, which conform to the principle of maximizing expected utility. It is argued that this approach offers more action guidance.