The approach to decision theory floated in my 1965 book is reviewed (I), challenged in various related ways (II–V) and defended, firstad hoc (II–IV) and then by a general argument of Ellery Ells's (VI). Finally, causal decision theory (in a version sketched in VII) is exhibited as a special case of my 1965 theory, according to the Eellsian argument.

This book deals not so much with statistical methods as with the central concept of chance, or statistical probability, which statistical theories apply to nature.

Newcomb's problem and similar cases show the need to incorporate causal distinctions into the theory of rational decision; the usual noncausal decision theory, though simpler, does not always give the right answers. I give my own version of causal decision theory, compare it with versions offered by several other authors, and suggest that the versions have more in common than meets the eye.

First published in 1982, Ellery Eells' original work on rational decision making had extensive implications for probability theorists, economists, statisticians and psychologists concerned with decision making and the employment of Bayesian principles. His analysis of the philosophical and psychological significance of Bayesian decision theories, causal decision theories and Newcomb's paradox continues to be influential in philosophy of science. His book is now revived for a new generation of readers and presented in a fresh twenty-first-century series livery, including a specially commissioned (...) preface written by Brian Skyrms, illuminating its continuing importance and relevance to philosophical enquiry. (shrink)

In past years, the traditional Bayesian theory of rational decision making, based on subjective calculations of expected utility, has faced powerful attack from philosophers such as David Lewis and Brian Skyrms, who advance an alternative causal decision theory. The test they present for the Bayesian is exemplified in the decision problem known as 'Newcomb's paradox' and in related decision problems and is held to support the prescriptions of the causal theory. As well as his conclusions, the concepts and methods of (...) Professor Eells introduces in the course of his analyses have extensive implications, not solely for probability theorists narrowly conceived, but for economists, statisticians and psychologists concerned with decision making and the employment of Bayesian principles. They and their students will, in addition, find the early chapters of great use as a background and introduction to the subject as a whole. (shrink)

Newcomb's paradox was first presented by Robert Nozick and has been discussed by a considerable number of writers. You are playing a game with a Being who seems to have extraordinary predictive powers. Before you are two boxes, in one of which you can see $1,000. The other is closed and you cannot see what it contains, but you know that the Being has put a million dollars into it if he has predicted that you will take it only, but (...) nothing if he has predicted that you will take both boxes; you may take either both boxes or the closed one only. The Being has correctly predicted the choices of all who have so far played with him. What should you do?Let us call the Being the seer, and his opponent the player. I should also like to reduce the amount that may, or may not, be in the closed box to $10,000. Nearly everyone could make good use of $1,000 and better use of $10,000 or $11,000, but it is hard to say whether a million dollars would be a blessing or a curse. (shrink)