Nelkin presents a simple and natural account of freedom and moral responsibility which responds to the great variety of challenges to the idea that we are free and responsible, before ultimately reaffirming our conception of ourselves as agents. Making Sense of Freedom and Responsibility begins with a defense of the rational abilities view, according to which one is responsible for an action if and only if one acts with the ability to recognize and act for good reasons. The view is (...) compatibilist -- that is, on the view defended, responsibility is compatible with determinism -- and one of its striking features is a certain asymmetry: it requires the ability to do otherwise for responsibility when actions are praiseworthy, but not when they are blameworthy. In defending and elaborating the view, Nelkin questions long-held assumptions such as those concerning the relation between fairness and blame and the nature of so-called reactive attitudes such as resentment and forgiveness. Her argument not only fits with a metaphysical picture of causation -- agent-causation -- often assumed to be available only to incompatibilist accounts, but receives positive support from the intuitively appealing Ought Implies Can Principle, and establishes a new interpretation of freedom and moral responsibility that dovetails with a compelling account of our inescapable commitments as rational agents. (shrink)

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

"[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.

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.

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)

According to the so-called ‘deliberation crowds out prediction’ thesis, while deliberating about what you’ll do, you cannot rationally have credences for what you’ll do – you cannot rationally have option-credences. Versions of the thesis have been defended by authors such as Spohn, Levi, Gilboa, Price, Louise, and others. After registering a number of concerns about the thesis, I rehearse and rebut many of the main arguments for it, grouped according to their main themes: agency, vacuity, betting, and decision-theoretical considerations. I (...) go on to suggest many possible theoretical roles for option-credences. -/- I locate the debate about the thesis in a broader discussion: Are there rational credence gaps – propositions to which one cannot rationally assign credences? If there are, they spell trouble for various foundations of Bayesian epistemology, including the usual ratio formula for conditional probability, conditionalization, decision theory, and independence. According to the thesis, credence gaps are completely mundane; they arise every time someone rationally deliberates. But these foundations are safe from any threat here, I contend, since the thesis is false. Deliberation welcomes prediction. (shrink)

When we deliberate about what to do, we appear to be free to decide on different options. Three accounts use ordinary beliefs to explain this apparent freedom—appealing to different types of ‘epistemic freedom’. When an agent has epistemic freedom, her evidence while deliberating does not determine what decision she makes. This ‘epistemic gap’ between her evidence and decision explains why her decision appears free. The varieties of epistemic freedom appealed to might look similar. But there is an important difference. Two (...) rely on an agent's ability to justifiably form beliefs unconstrained by evidence, and identify decisions as beliefs—either beliefs about acts or about decisions. But, when used to explain apparent freedom, these accounts face serious problems: they imply that agents have epistemic freedom over evidence-based beliefs, and rely on a faulty notion of justification. Underlying these troubles, it turns out that these accounts presuppose an unexplained apparent ability to form different beliefs. A third variety of epistemic freedom uses ignorance conditions instead (Levi and Kapitan). We appear free partly because we’re ignorant of what we’ll decide. Ignorance-based accounts avoid the above problems, and remain a promising alternative. (shrink)

An alleged counterexample to causal decision theory, put forward by Andy Egan, is studied in some detail. It is argued that Egan rejects the evaluation of causal decision theory on the basis of a description of the decision situation that is different from—indeed inconsistent with—the description on which causal decision theory makes its evaluation. So the example is not a counterexample to causal decision theory. Nevertheless, the example shows that causal decision theory can recommend unratifiable acts which presents a problem (...) in the dynamics of intentions. It is argued that we can defuse this problem if we hold that decision theory is a theory of rational decision making rather than a theory of rational acts. It is shown how decisions can have epistemic side-effects that are not mediated by the act and that there are cases where one can only bring oneself to perform the best act by updating by imaging rather than by conditioning. This provides a pragmatic argument for updating by imaging rather than by conditioning in these cases. (shrink)

This paper explores the possibility that causal decision theory can be formulated in terms of probabilities of conditionals. It is argued that a generalized Stalnaker semantics in combination with an underlying branching time structure not only provides the basis for a plausible account of the semantics of indicative conditionals, but also that the resulting conditionals have properties that make them well-suited as a basis for formulating causal decision theory. Decision theory (at least if we omit the frills) is not an (...) esoteric science, however unfamiliar it may seem to an outsider. Rather it is a systematic exposition of the consequences of certain well-chosen platitudes about belief, desire, preference and choice. It is the very core of our common-sense theory of persons, dissected out and elegantly systematized. (David Lewis, Synthese 23:331–344, 1974, p. 337). A small distortion in the analysis of the conditional may create spurious problems with the analysis of other concepts. So if the facts about usage favor one among a number of subtly different theories, it may be important to determine which one it is. (Robert Stalnaker, A Defense of Conditional Excluded Middle, pp. 87–104, 1980, p. 87). (shrink)

Causal decision theory (CDT) cares only about the effects of a contemplated act, not its causes. The article constructs a case in which CDT consequently recommends a bet that the agent is certain to lose, rather than a bet that she is certain to win. CDT is plainly giving wrong advice in this case. It therefore stands refuted. 1 The Argument2 The Argument in More Detail2.1 The betting mechanism2.2 Soft determinism2.3 The content of P 2.4 The argument again3 The Descriptive (...) Premise3.1 Causal decision theory3.2 Causal decision theory prefers A14 The Normative Premise5 Objections5.1 Table 1 and Table 2 are misleading5.2 The agency theory of causation5.3 The payment mechanism5.4 Newcomb’s problem5.5 Against the normative premise5.6 Drop soft determinism. (shrink)

The essay presents a novel counterexample to Causal Decision Theory (CDT). Its interest is that it generates a case in which CDT violates the very principles that motivated it in the first place. The essay argues that the objection applies to all extant formulations of CDT and that the only way out for that theory is a modification of it that entails incompatibilism. The essay invites the reader to find this consequence of CDT a reason to reject it.

Most philosophers agree that causal knowledge is essential to decision-making: agents should choose from the available options those that probably cause the outcomes that they want. This book argues against this theory and in favour of evidential or Bayesian decision theory, which emphasises the symptomatic value of options over their causal role. It examines a variety of settings, including economic theory, quantum mechanics and philosophical thought-experiments, where causal knowledge seems to make a practical difference. The arguments make novel use of (...) machinery from other areas of philosophical inquiry, including first-person epistemology and the free will debate. The book also illustrates the applicability of decision theory itself to questions about the direction of time and the special epistemic status of agents. (shrink)

If my ability to react freely is constrained by forces beyond my control, am I still morally responsible for the things I do? The question of whether, how and to what extent we are responsible for our own actions has always been central to debates in philosophy and theology, and has been the subject of much recent research in cognitive science. And for good reason- the views we take on free will affect the choices we make as individuals, the moral (...) judgments we make of others, and they will inform public policy. Michael McKenna's text introduces this important subject with remarkable clarity, offering the first comprehensive overview of both incompatibilist and compatibilist stances. He begins by motivating both viewpoints, then provides classical accounts of each before giving students an in-depth examination of current scholarship in the free will debate. Topics covered include: the nature of free will the nature of determinism the nature of moral responsibility arguments for the incompatibility of free will and determinism arguments of the compatibility of free will and determinism libertarian theories of free will and moral responsibility compatibilist theories of free will and moral responsibility hard determinist and hard incompatibilist theories. (shrink)

J. Howard Sobel has long been recognized as an important figure in philosophical discussions of rational decision. He has done much to help formulate the concept of causal decision theory. In this volume of essays Sobel explores the Bayesian idea that rational actions maximize expected values, where an action's expected value is a weighted average of its agent's values for its possible total outcomes. Newcomb's Problem and The Prisoner's Dilemma are discussed, and Allais-type puzzles are viewed from the perspective of (...) causal world Bayesianism. The author establishes principles for distinguishing options in decision problems, and studies ways in which perfectly rational causal maximizers can be capable of resolute choices. Sobel also views critically Gauthier's revisionist ideas about maximizing rationality. This collection will be a desideratum for anyone working in the field of rational choice theory, whether in philosophy, economics, political science, psychology or statistics. Howard Sobel's work in decision theory is certainly among the most important, interesting and challenging that is being done by philosophers. (shrink)