Classic analysis of the subject and the development of personal probability; one of the greatest controversies in modern statistcal thought.

The aim of this paper is to sketch a theory of justified belief. What I have in mind is an explanatory theory, one that explains in a general way why certain beliefs are counted as justified and others as unjustified. Unlike some traditional approaches, I do not try to prescribe standards for justification that differ from, or improve upon, our ordinary standards. I merely try to explicate the ordinary standards, which are, I believe, quite different from those of many classical, (...) e. g., ‘Cartesian’, accounts. (shrink)

In “Bayesianism, Infinite Decisions, and Binding”, Arntzenius et al. (Mind 113:251–283, 2004 ) present cases in which agents who cannot bind themselves are driven by standard decision theory to choose sequences of actions with disastrous consequences. They defend standard decision theory by arguing that if a decision rule leads agents to disaster only when they cannot bind themselves, this should not be taken to be a mark against the decision rule. I show that this claim has surprising implications for a (...) number of other debates in decision theory. I then assess the plausibility of this claim, and suggest that it should be rejected. (shrink)

"[This book] proposes new foundations for the Bayesian principle of rational action, and goes on to develop a new logic of desirability and probabtility."—Frederic Schick, _Journal of Philosophy_.

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

Act-utilitarianism comes in two standard varieties: ‘subjective’ act-utilitarianism, which tells agents to attempt to maximize utility directly, and ‘objective’ act-utilitarianism, which permits agents to use non-utilitarian decision-making procedures. This article argues that objective actutilitarianism is exposed to a dilemma. On one horn of it is the contention that objective act-utilitarianism makes inconsistent claims about the rightness of acts. On the other horn of it is the contention that objective act-utilitarianism collapses back into what is, essentially, subjective act-utilitarianism. Three objective act-utilitarian (...) responses to this dilemma are explored and rejected. The recommended conclusion is that a consistent utilitarian must either embrace subjective act-utilitarianism, or abandon act-utilitarianism altogether. Key Words: act-utilitarianism • subjective • objective • decision-making procedure • criterion of rightness • dilemma. (shrink)

Many assume that we can be responsible only what is voluntary. This leads to puzzlement about our responsibility for our beliefs, since beliefs seem not to be voluntary. I argue against the initial assumption, presenting an account of responsibility and of voluntariness according to which, not only is voluntariness not required for responsibility, but the feature which renders an attitude a fundamental object of responsibility (that the attitude embodies one’s take on the world and one’s place in it) also guarantees (...) that it could not be voluntary. It turns out, then, that, for failing to be voluntary, beliefs are a central example of the sort of thing for which we are most fundamentally responsible. (shrink)

La autora presenta algunas criticas generales al proyecto de reducir las leyes causales a probabilidades. Además, muestra que las leyes causales son imprescindibles para poder diferenciar las strategias efectivas de las que no lo son y da un criterio para considerar cuando podemos deducir causalidad a través de datos estadísticos.

Challenging, with several powerful arguments, some of our deepest beliefs about rationality, morality, and personal identity, Parfit claims that we have a false view about our own nature. It is often rational to act against our own best interersts, he argues, and most of us have moral views that are self-defeating. We often act wrongly, although we know there will be no one with serious grounds for complaint, and when we consider future generations it is very hard to avoid conclusions (...) that most of us will find very disturbing. (shrink)

I hope to show that, although belief is subject to two quite robust forms of agency, "believing at will" is impossible; one cannot believe in the way one ordinarily acts. Further, the same is true of intention: although intention is subject to two quite robust forms of agency, the features of belief that render believing less than voluntary are present for intention, as well. It turns out, perhaps surprisingly, that you can no more intend at will than believe at will.

The standard formulation of Newcomb's problem compares evidential and causal conceptions of expected utility, with those maximizing evidential expected utility tending to end up far richer. Thus, in a world in which agents face Newcomb problems, the evidential decision theorist might ask the causal decision theorist: "if you're so smart, why ain’cha rich?” Ultimately, however, the expected riches of evidential decision theorists in Newcomb problems do not vindicate their theory, because their success does not generalize. Consider a theory that allows (...) the agents who employ it to end up rich in worlds containing Newcomb problems and continues to outperform in other cases. This type of theory, which I call a “success-first” decision theory, is motivated by the desire to draw a tighter connection between rationality and success, rather than to support any particular account of expected utility. The primary aim of this paper is to provide a comprehensive justification of success-first decision theories as accounts of rational decision. I locate this justification in an experimental approach to decision theory supported by the aims of methodological naturalism. (shrink)

Contemporary virtue epistemology (hereafter ‘VE’) is a diverse collection of approaches to epistemology. At least two central tendencies are discernible among the approaches. First, they view epistemology as a normative discipline. Second, they view intellectual agents and communities as the primary focus of epistemic evaluation, with a focus on the intellectual virtues and vices embodied in and expressed by these agents and communities. -/- This entry introduces many of the most important results of the contemporary VE research program. These include (...) novel attempts to resolve longstanding disputes, solve perennial problems, grapple with novel challenges, and expand epistemology’s horizons. In the process, it reveals the diversity within VE. Beyond sharing the two unifying commitments mentioned above, its practitioners diverge over the nature of intellectual virtues, which questions to ask, and which methods to use. -/- It will be helpful to note some terminology before proceeding. First, we use ‘cognitive’, ‘epistemic’ and ‘intellectual’ synonymously. Second, we often use ‘normative’ broadly to include not only norms and rules, but also duties and values. Finally, ‘practitioners’ names contemporary virtue epistemologists. (shrink)

An argument against the bias towards the near; how a defence of temporal neutrality is not a defence of S; an appeal to inconsistency; why we should reject S and accept CP.

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)

There are two boxes in front of you and you are asked to choose between taking only box B or taking both box A and box B. Box A contains $ 1,000. Box B will contain either nothing or $ 1,000,000. What B will contain is (or will be) determined by Predictor, who has an excellent track record of predicting your choices. There are two possibilities. Either Predictor has already made his move by predicting your choice and putting a million (...) dollars in B iff he predicted that you will take only B (like in the standard Newcomb problem); or else Predictor has not yet made his move but will wait and observe what box you choose and then put a million dollars in B iff you take only B. In cases like this, Predictor makes his move before the subject roughly half of the time. However, there is a Metapredictor, who has an excellent track record of predicting Predictor’s choices as well as your own. You know all this. Metapredictor informs you of the following truth functional: Either you choose A and B, and Predictor will make his move after you make your choice; or else you choose only B, and Predictor has already made his choice. Now, what do you choose? (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)

The theory of morality we can call full rule - consequentialism selects rules solely in terms of the goodness of their consequences and then claims that these rules determine which kinds of acts are morally wrong. George Berkeley was arguably the first rule -consequentialist. He wrote, “In framing the general laws of nature, it is granted we must be entirely guided by the public good of mankind, but not in the ordinary moral actions of our lives. … The rule is (...) framed with respect to the good of mankind; but our practice must be always shaped immediately by the rule.” Writers often classed as rule -consequentialists include Austin 1832; Harrod 1936; Toulmin 1950; Urmson 1953; Harrison 1953; Mabbott 1953; Singer 1955; 1961; and most prominently Brandt 1959; 1963; 1967; 1979; 1989; 1996; and Harsanyi 1977; 1982; 1993. See also Rawls 1955; Hospers 1972; Haslett 1987; 1994, ch. 1; 2000; Attfield 1987, 103-12; Barrow 1991, ch. 6; Johnson 1991; Riley 1998; 2000; Shaw 1999; and Hooker 2000. Whether J. S. Mill's ethics was rule -consequentialist is controversial. (shrink)

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)

This book makes a significant contribution to the standard decision theory, that is, the theory of choice built around the principle of maximizing expected utility, both to its causal version and to the more traditional noncausal approach. The author’s success in clarifying the foundations of the standard decision theory in general, and causal decision theory in particular, also makes the book uniquely suitable for a person whose research in philosophy has led her to want to learn about contemporary decision theory. (...) The book presupposes some mathematical sophistication, and it contains more philosophical and mathematical argumentation per page than may be suitable for an undergraduate level course; but it stands out as an ideal textbook for a graduate-level course focused on the foundations of the standard decision theory. (shrink)

Many philosophers (myself included) have been converted to causal decision theory by something like the following line of argument: Evidential decision theory endorses irrational courses of action in a range of examples, and endorses “an irrational policy of managing the news”. These are fatal problems for evidential decision theory. Causal decision theory delivers the right results in the troublesome examples, and does not endorse this kind of irrational news-managing. So we should give up evidential decision theory, and be causal decision (...) theorists instead. Unfortunately, causal decision theory has its own family of problematic examples for which it endorses irrational courses of action, and its own irrational policy that it is committed to endorsing. These are, I think, fatal problems for causal decision theory. I wish that I had another theory to offer in its place. (shrink)

Proponents of causal decision theories argue that classical Bayesian decision theory (BDT) gives the wrong advice in certain types of cases, of which the clearest and commonest are the medical Newcomb problems. I defend BDT, invoking a familiar principle of statistical inference to show that in such cases a free agent cannot take the contemplated action to be probabilistically relevant to its causes (so that BDT gives the right answer). I argue that my defence does better than those of Ellery (...) Eells and Richard Jeffrey; and that it applies, where necessary, to other types of Newcomb problem. (shrink)

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.

Clark Glymour, together with his students Peter Spirtes and Richard Scheines, did pioneering work on graphical causal models . One of the central advances provided by these models is the ability to simply represent the effects of interventions. In an elegant paper , Glymour and his student Christopher Meek applied these methods to problems in decision theory. One of the morals they drew was that causal decision theory should be understood in terms of interventions. I revisit their proposal, and extend (...) the analysis by showing how graphical causal models might be used to address decision problems that arise in “exotic” situations, such as those involving crystal balls or time travelers. (shrink)

Derek Parfit, Philip Pettit and Michael Smith defend a version of consequentialism that covers everything. I argue that this version of consequentialism is false. Consequentialism, I argue, can only cover things that belong to a combination of things that agents can bring about.

Suppose that two geysers, about one mile apart, erupt at irregular intervals, but usually erupt almost exactly at the same time. One would suspect that they come from a common source, or at least that there is a common cause of their eruptions. And this common cause surely acts before both eruptions take place. This idea, that simultaneous correlated events must have prior common causes, was first made precise by Hans Reichenbach (Reichenbach 1956). It can be used to infer the (...) existence of unobserved and unobservable events, and to infer causal relations from statistical relations. Unfortunately it does not appear to be universally valid, nor is there agreement as to the circumstances in which it is valid. (shrink)