This book defends the view that any adequate account of rational decision making must take a decision maker's beliefs about causal relations into account. The early chapters of the book introduce the non-specialist to the rudiments of expected utility theory. The major technical advance offered by the book is a 'representation theorem' that shows that both causal decision theory and its main rival, Richard Jeffrey's logic of decision, are both instances of a more general conditional decision theory. The book solves (...) a long-standing problem for Jeffrey's theory by showing for the first time how to obtain a unique utility and probability representation for preferences and judgements of comparative likelihood. The book also contains a major new discussion of what it means to suppose that some event occurs or that some proposition is true. The most complete and robust defence of causal decision theory available. (shrink)

Is morality rational? In this book Gauthier argues that moral principles are principles of rational choice. He proposes a principle whereby choice is made on an agreed basis of cooperation, rather than according to what would give an individual the greatest expectation of value. He shows that such a principle not only ensures mutual benefit and fairness, thus satisfying the standards of morality, but also that each person may actually expect greater utility by adhering to morality, even though the choice (...) did not have that end primarily in view. In resolving what may appear to be a paradox, the author establishes morals on the firm foundation of reason. Gauthier's argument includes an account of value, linking it to preference and utility; a discussion of the curcumstances in which morality is unnecessary; and an application of morals by agreement to relations between peoples at different levels of development and different generations. Finally, he reflects on the assumptions about individuality and community made by his account of rationality and morality. (shrink)

Examples growing out of the Newcomb problem have convinced many people that decision theory should proceed in terms of some kind of causal probability. I endorse this view and define and investigate a variety of causal probability. My definition is related to Skyrms' definition, but proceeds in terms of objective probabilities rather than subjective probabilities and avoids taking causal dependence as a primitive concept.

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.