If modus ponens is valid, then you should take up smoking.

This paper explores the idea that a semantics for ‘ought’ should be neutral between different ways of deciding what an agent ought to do in a situation. While the idea is, I argue, well-motivated, taking it seriously leads to surprising, even paradoxical, problems for theorizing about the meaning of ‘ought’. This paper describes and defends one strategy—a form of Expressivism for the modal ‘ought’—for navigating these problems.

I apply some of the lessons from quantum theory, in particular from Bell’s theorem, to a debate on the foundations of decision theory and causation. By tracing a formal analogy between the basic assumptions of causal decision theory (CDT)—which was developed partly in response to Newcomb’s problem— and those of a local hidden variable theory in the context of quantum mechanics, I show that an agent who acts according to CDT and gives any nonzero credence to some possible causal interpretations (...) underlying quantum phenomena should bet against quantum mechanics in some feasible game scenarios involving entangled systems, no matter what evidence they acquire. As a consequence, either the most accepted version of decision theory is wrong, or it provides a practical distinction, in terms of the prescribed behaviour of rational agents, between some metaphysical hypotheses regarding the causal structure underlying quantum mechanics. (shrink)

Kratzer semantics for modals and conditionals generates the prediction that sentences of the form if p, ought p are trivially true. As Frank and Zvolenszky show, for certain flavors of modality, like deontic modality, this prediction is false. I explain some conservative solutions to the problem, and then argue that they are inadequate to account for puzzle cases involving self-frustrating oughts. These cases illustrate a general problem: there are two forms of information-sensitivity in deontic modals. Even generalizations of Kratzer semantics (...) that predict these two roles for information, e.g. Kolodny and MacFarlane, predict that they vary together. I propose a generalization of Kratzer semantics that allows the two roles for information to vary independently of each other. (shrink)

The logic of dominance arguments is analyzed using two different kinds of conditionals: indicative (epistemic) and subjunctive (counter-factual). It is shown that on the indicative interpretation an assumption of independence is needed for a dominance argument to go through. It is also shown that on the subjunctive interpretation no assumption of independence is needed once the standard premises of the dominance argument are true, but that independence plays an important role in arguing for the truth of the premises of the (...) dominance argument. A key feature of the analysis is the interpretation of the doubly conditional comparative "I will get a better outcome if A than if B" which is taken to have the structure "(the outcome if A) is better than (the outcome if B)". (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)

An attractive approach to the semantic paradoxes holds that cases of semantic pathology give rise to indeterminacy. What attitude should a rational agent have toward a proposition that it takes to be indeterminate in this sense? Orthodoxy holds that rationality requires that an agent disbelieve such a proposition. I argue that a rational agent should be such that it is indeterminate whether it believes the proposition in question. For rational agents, indeterminacy in the objects of their attitudes will filter up (...) to the attitudes themselves. (shrink)

The nature of evidence is a problem for epistemology, but I argue that this problem intersects with normative decision theory in a way that I think is underappreciated. Among some decision theorists, there is a presumption that one can always ignore the nature of evidence while theorizing about principles of rational choice. In slogan form: decision theory only cares about the credences agents actually have, not the credences they should have. I argue against this presumption. In particular, I argue that (...) if evidence can be unspecific, then an alleged counterexample to causal decision theory fails. This implies that what theory of decision we think is true may depend on our opinions regarding the nature of evidence. Even when we are theorizing about subjective theories of rationality, we cannot set aside questions about the objective nature of evidence. (shrink)

There is an ongoing debate in the philosophical literature whether the conditionals that are central to deliberation are subjunctive or indicative conditionals and, if the latter, what semantics of the indicative conditional is compatible with the role that conditionals play in deliberation. We propose a possible-world semantics where conditionals of the form “if I take action _a_ the outcome will be _x_” are interpreted as material conditionals. The proposed framework is illustrated with familiar examples and both qualitative and probabilistic beliefs (...) are considered. Issues such as common-cause cases and ‘Egan-style’ cases are discussed. (shrink)

In a seminal paper, Aumann (1987, Econometrica 55, 1–18) showed how the choices of rational players could be analyzed in a unified state space framework. His innovation was to include the choices of the players in the description of the states, thus abolishing Savage’s (1954, The Foundations of Statistics. Wiley, New York) distinction between acts and consequences. But this simplification comes at a price: Aumann’s notion of Bayes rationality does not allow players to evaluate what would happen were they to (...) deviate from their actual choices. We show how the addition of a causal structure to the framework enables us to analyze such counterfactual statements, and use it to introduce a notion of causal rationality. Under a plausible causal independence condition, the two notions are shown to be equivalent. If we are prepared to accept this condition we can dispense with the causal apparatus and retain Aumann’s original framework. (shrink)

This paper is about two requirements on wish reports whose interaction motivates a novel semantics for these ascriptions. The first requirement concerns the ambiguities that arise when determiner phrases, such as definite descriptions, interact with ‘wish’. More specifically, several theorists have recently argued that attitude ascriptions featuring counterfactual attitude verbs license interpretations on which the determiner phrase is interpreted relative to the subject’s beliefs. The second requirement involves the fact that desire reports in general require decision-theoretic notions for their analysis. (...) The current study is motivated by the fact that no existing account captures both of these aspects of wishing. I develop a semantics for wish reports that makes available belief-relative readings but also allows decision-theoretic notions to play a role in shaping the truth conditions of these ascriptions. The general idea is that we can analyze wishing in terms of a two-dimensional notion of expected utility. (shrink)

Benchmark theory , introduced by Ralph Wedgwood, departs from decision theories of pure expectation maximization like evidential decision theory and causal decision theory and instead ranks actions according to the desirability of an outcome they produce in some state of affairs compared to a standard—a benchmark—for that state of affairs. Wedgwood motivates BT through what he terms Gandalf’s principle, that the merits of an action in a given state should be evaluated relative only to the performances of other actions in (...) that state, and not to their performances in other states. Although BT succeeds in selecting intuitively rational actions in a number of cases—including some in which EDT or CDT seem to go wrong—it places constraints on rational decision-making that either lack motivation or are untenable. Specifically, I argue that as it stands BT is committed both to endorsing and rejecting the independence of irrelevant alternatives. Furthermore its requirement that weakly dominated actions be excluded from consideration of rational action lacks motivation and threatens to collide with traditional game theory. In the final section of the paper, I construct a counterexample to BT. (shrink)

Causal decision theory is one of our most prominent theories of rational choice and the “why ain’cha rich?” argument is one of the most prominent objections to this theory. According to WAR, CDT is not an adequate theory of rational choice because it leads agents to make decisions that foreseeably leave them less well off than agents that decide in some other manner. Some philosophers take WAR to decisively undermine CDT. On the other hand, others take WAR to fail to (...) resolve the debate over CDT’s adequacy. In this paper, I will defend this second view: WAR does not resolve the debate at hand but instead leads to deadlock. Then, in the second half of this paper, I will show that this deadlock is not broken by a recent variant on WAR due to Caspar Hare and Brian Hedden. Not only does this result have implications for the debate over CDT’s adequacy but this discussion also casts light on the broader success/rationality link. (shrink)

The more you think about it, the more baffling Newcomb's Problem becomes. To most people, at first it is obvious which solution is correct, but their confidence can be eroded easily. Only a puzzled few are torn between the two right from the start, and for years so was I. But at last, thanks to a certain metaargument, one solution came to seem obvious to me. And yet, imagining myself actually faced with Newcomb's choice, I started to worry that I (...) might experience just enough last-minute ambivalence to unsettle my confidence in that argument. Fortunately, I have found a strategy to ensure making the right choice when the chips are down.Not only is Newcomb's Problem puzzling in its own right, it is philosophically significant. The appeal of both solutions reflects a conflict between two plausible conceptions of rational choice. In making a decision, should one consider all of its probabilistic consequences or only its causal consequences? Each conception has its supporters, but some philosophers find them both defensible and see no hope of resolving the conflict. I think the conflict can be resolved, at least in the context of Newcomb's Problem, by properly assessing the relevant counterfactual conditionals. (shrink)

Decision theory is founded on the principle that we ought to take the action that has the maximum expected value from among actions we are in a position to take. But prior to the notion of expected value is the notion of the actual value of that action: roughly, a measure of the good outcomes you would in fact procure if you were to take it. Surprisingly many decision theories operate without an analysis of actual value. I offer a definition (...) of actual value, and show that a form of decision theory due to Stalnaker can be reformulated so as to be in line with the edict to maximize expected value. By contrast, I show that there is no quantity — given by my definition or otherwise — that plays the role of actual value in Jeffrey's decision theory. (shrink)

I argue that standard decision theories, namely causal decision theory and evidential decision theory, both are unsatisfactory. I devise a new decision theory, from which, under certain conditions, standard game theory can be derived.

We pose and resolve several vexing decision theoretic puzzles. Some are variants of existing puzzles, such as 'Trumped' (Arntzenius and McCarthy 1997), 'Rouble trouble' (Arntzenius and Barrett 1999), 'The airtight Dutch book' (McGee 1999), and 'The two envelopes puzzle' (Broome 1995). Others are new. A unified resolution of the puzzles shows that Dutch book arguments have no force in infinite cases. It thereby provides evidence that reasonable utility functions may be unbounded and that reasonable credence functions need not be countably (...) additive. The resolution also shows that when infinitely many decisions are involved, the difference between making the decisions simultaneously and making them sequentially can be the difference between riches and ruin. Finally, the resolution reveals a new way in which the ability to make binding commitments can save perfectly rational agents from sure losses. (shrink)

The primary aim of this paper is the presentation of a foundation for causal decision theory. This is worth doing because causal decision theory (CDT) is philosophically the most adequate rational decision theory now available. I will not defend that claim here by elaborate comparison of the theory with all its competitors, but by providing the foundation. This puts the theory on an equal footing with competitors for which foundations have already been given. It turns out that it will also (...) produce a reply to the most serious objections made so far against CDT and against the particular version of CDT I will defend. (shrink)

Opponents of Causal Decision Theory (CDT) sometimes claim (i) that it gives the wrong advice in Egan-style cases, where the CDT-endorsed act brings news that it causes a bad outcome; (ii) that CDT gives the right advice in Newcomb cases, where it is known in advance that the CDT-act causes you to be richer than the alternative. This paper argues that (i) and (ii) cannot both be true if rational preference over acts is transitive.

It is intuitively attractive to think that it makes a difference in Newcomb’s problem whether or not the predictor is infallible, in the sense of being certainly actually correct. This paper argues that that view is irrational and manifests a well-documented cognitive illusion.

has offered evidential decision theorists a defence against the charge that they make unintuitive recommendations for cases like Newcomb's Problem. He says that when conditional probabilities are assessed from the agent's point of view, evidential decision theory makes the same recommendation as intuition. I argue that calculating the probabilities in Price's way leads to no recommendation. It condemns the agent to perpetual oscillation between different options. Price's Argument Instability Objections Conclusion.

You should rather play hide-and-seek against someone who cannot predict where you hide than against someone who can, as the article illustrates in connection with a high-stakes example. Causal Decision Theory denies this. So Causal Decision Theory is false.

Sophisticated ‘tickle’-style defences of Evidential Decision Theory take your motivational state to screen off your act from any state that is causally independent of it, thus ensuring that EDT and CDT converge. That leads to unacceptable instability in cases in which the correct action is obvious. We need a more liberal conception of what the agent controls. It follows that an ordinary deliberator should sometimes consider the past and not only the future to be subject to her present choice.

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 paper argues that on three out of eight possible hypotheses about the EPR experiment we can construct novel and realistic decision problems on which (a) Causal Decision Theory and Evidential Decision Theory conflict (b) Causal Decision Theory and the EPR statistics conflict. We infer that anyone who fully accepts any of these three hypotheses has strong reasons to reject Causal Decision Theory. Finally, we extend the original construction to show that anyone who gives any of the three hypotheses any (...) non-zero credence has strong reasons to reject Causal Decision Theory. However, we concede that no version of the Many Worlds Interpretation (Vaidman, in Zalta, E.N. (ed.), Stanford Encyclopaedia of Philosophy 2014) gives rise to the conflicts that we point out. (shrink)

The best-known argument for Evidential Decision Theory (EDT) is the ‘Why ain’cha rich?’ challenge to rival Causal Decision Theory (CDT). The basis for this challenge is that in Newcomb-like situations, acts that conform to EDT may be known in advance to have the better return than acts that conform to CDT. Frank Arntzenius has recently proposed an ingenious counter argument, based on an example in which, he claims, it is predictable in advance that acts that conform to EDT will do (...) less well than acts that conform to CDT. We raise two objections to Arntzenius’s example. We argue, first, that the example is subtly incoherent, in a way that undermines its effectiveness against EDT; and, second, that the example relies on calculating the average return over an inappropriate population of acts. (shrink)

Judging an act’s causal efficacy plays a crucial role in causal decision theory. A recent development appeals to the causal modeling framework with an emphasis on the analysis of intervention based on the causal Bayes net for clarifying what causally depends on our acts. However, few writers have focused on exploring the usefulness of extending structural causal models to decision problems that are not ideal for intervention analysis. The thesis concludes that structural models provide a more general framework for rational (...) decision makers. (shrink)

In Newcomb’s paradox you can choose to receive either the contents of a particular closed box, or the contents of both that closed box and another one. Before you choose though, an antagonist uses a prediction algorithm to accurately deduce your choice, and uses that deduction to fill the two boxes. The way they do this guarantees that you made the wrong choice. Newcomb’s paradox is that game theory’s expected utility and dominance principles appear to provide conflicting recommendations for what (...) you should choose. Here we show that the conflicting recommendations assume different probabilistic structures relating your choice and the algorithm’s prediction. This resolves the paradox: the reason there appears to be two conflicting recommendations is that the probabilistic structure relating the problem’s random variables is open to two, conflicting interpretations. We then show that the accuracy of the prediction algorithm in Newcomb’s paradox, the focus of much previous work, is irrelevant. We end by showing that Newcomb’s paradox is time-reversal invariant; both the paradox and its resolution are unchanged if the algorithm makes its ‘prediction’ after you make your choice rather than before. (shrink)

Until recently, many philosophers took Causal Decision Theory to be more successful than its rival, Evidential Decision Theory. Things have changed, however, with a renewed concern that cases involving an extreme form of decision instability are counterexamples to CDT :392–403, 1984; Egan in Philos Rev 116:93–114, 2007). Most prominent among those cases of extreme decision instability is the Psychopath Button, due to Andy Egan; in that case, CDT recommends a seemingly absurd act that almost certainly results in your death. This (...) renewed attention to decision instability has spurned an array of modifications to and rejections of CDT. I argue, however, that the Psychopath Button and its ilk are no counterexamples to CDT. That is, given the causalist’s commitments in Newcomb Problems, they already have the tools to justify CDT’s verdict in Egan-style cases of extreme decision instability. I first argue that there is no reason to think the Psychopath Button is a counterexample to CDT; in particular, many philosophers have placed too much weight on pre-theoretic intuition in Egan-cases, and apart from pre-theoretic intuition, arguments against CDT in cases of extreme decision instability are flawed. My second claim is that the causalist can provide good reasons for following CDT in cases of extreme decision instability. I present a new case, the Two Button Defense, that highlights precisely why the causalist can reasonably follow CDT in even the Psychopath Button. CDT therefore stands as a viable decision theory, without need for modification, restriction, or rejection. (shrink)

In October 1993, a survey of health care agency administrators was undertaken shortly after they had experienced two sudden reductions in public funding. The purpose of this investigation was to gain insight into the role of ethics in health administrator decision making. A mail questionnaire was designed for this purpose. Descriptive statistics and content analysis were used to summarize the data. Staff reductions and bed closures were the two most frequently reported mechanisms for addressing the funding reductions. Most administrators did (...) not believe that these changes would have a negative public impact. In contrast, the majority indicated that future changes in reaction to additional funding reductions would have a negative public impact. Approximately one-third of the administrators reported ethics to be an element of recent administrative decision making, and one-half could foresee that ethics would be important in the future if reductions continued. These findings are discussed in relation to ethics. Issues for additional research are outlined. (shrink)

The 'Why ain'cha rich?' argument for one-boxing in Newcomb's problem allegedly vindicates evidential decision theory and undermines causal decision theory. But there is a good response to the argument on behalf of causal decision theory. I develop this response. Then I pose a new problem and use it to give a new 'Why ain'cha rich?' argument. Unlike the old argument, the new argument targets evidential decision theory. And unlike the old argument, the new argument is sound.

Suppose that you have to take a test tomorrow but you do not want to study. Unfortunately you should study, since you care about passing and you expect to pass only if you study. Is there anything you can do to make it the case that you should not study? Is there any way for you to ‘rationalize’ slacking off? I suggest that such rationalization is impossible. Then I show that if evidential decision theory is true, rationalization is not only (...) possible but sometimes advisable. (shrink)

Expected-utility theory advances representation theorems that do not take the risk an act generates as a consequence of the act. However, a principle of expected-utility maximization that explains the rationality of preferences among acts must, for normative accuracy, take the act’s risk as a consequence of the act if the agent cares about the risk. I defend this conclusion against the charge that taking an act’s consequences to comprehend all the agent cares about trivializes the principle of expected-utility maximization.

There are arguments which purport to rebut psychological determinism by appealing to its alleged incompatibility with rationality. I argue that they all fail. Against Davidson, I argue that rationality does not preclude the existence of psychological laws. Against Popper, I argue that rationality is compatible with the possibility of predicting human actions. Against Schlesinger, I claim that Newcomb's problem cannot be invoked to show that human actions are unpredictable. Having vindicated the possibility of a rationally-based theory of action, I consider (...) the form it might take. (shrink)

Causal decision theory produces decision instability in cases such as Death in Damascus where a decision itself provides evidence concerning the utility of options. Several authors have proposed ways of handling this instability. William Harper (1985 and 1986) advances one of the most elegant proposals. He recommends maximizing causal expected utility among the options that are causally ratifiable. Unfortunately, Harper's proposal imposes certain restrictions; for instance, the restriction that mixed strategies are freely available. To obtain a completely general method of (...) handling decision instability, I step outside the confines of pure causal decision theory. I introduce a new kind of backtracking expected utility and propose maximizing it among the options that are causally ratifiable. In other words, I propose a hierarchical maximization of (1) conditional causal expected utility and (2) the new backtracking expected utility. I support this proposal with some intuitive considerations concerning the distinction between optimality and conditional optimality. And I prove that the proposal yields a solution in every finite decision problem. (shrink)

In some decision problems adoption of an option furnishes evidence about the option's consequences. Rational decisions take account of that evidence, although it makes an option's adoption changes the option's expected utility.

The expected utility of an option for a decision maker is defined with respect to probability and utility functions that represent the decision maker’s beliefs and desires. Therefore, as the decision maker’s beliefs and desires change, the expected utility of an opinion may change. Some options are such that their realizations change beliefs and desires in ways that change the expected utilities of the options. If a decision is made among options that include one or more of these special options, (...) I call it a decision made in a dynamic setting.The rule to maximize expected utility, MEU, is insufficient for decisions in dynamic settings. It does not say how to take account of information about the way in which the realization of an option would change the expected utility of the option. (shrink)

A common type of change in science occurs as theorists generalize a model of a phenomenon by removing some idealizations of the model. This type of change occurs in the decision sciences and also in the normative branch of the decision sciences that treats rational choice. After presenting a general ac-count of model generalization, the paper illustrates generalization of models in normative decision theory. The principal illustration generalizes a standard model of rational choice by removing the idealization that deliberation has (...) no cost. (shrink)

This article proposes a new theory of rational decision, distinct from both causal decision theory (CDT) and evidential decision theory (EDT). First, some intuitive counterexamples to CDT and EDT are presented. Then the motivation for the new theory is given: the correct theory of rational decision will resemble CDT in that it will not be sensitive to any comparisons of absolute levels of value across different states of nature, but only to comparisons of the differences in value between the available (...) options within states of nature; however, the correct theory will also resemble EDT in that it will rely on conditional probabilities (not unconditional probabilities). The new theory gives a prominent role to the notion of a “benchmark” for each state of nature, by comparison with which the value of the available options in that state of nature are measured, and so it has been called the Benchmark Theory (BT). It is argued that BT gives the right verdict on the cases that seem to be counterexamples to CDT and EDT. Finally, some objections to BT are considered and answered. (shrink)

It is commonly thought, in line with the position defended in an influential paper by David Lewis, that the decision problems faced in the prisoner’s dilemma and the Newcomb situation are essentially the same problem. José Luis Bermúdez has recently attacked the case Lewis makes for this claim. While I think the claim is false, I contend that Bermúdez’s reason for rejecting Lewis’s argument is inadequate, and then outline what I take to be a better reason for doing so.

In this paper I explore a version of standard (expected utility) decision theory in which the probability parameter is interpreted as an objective chance believed by agents to obtain and values of this parameter are fixed by indicative conditionals linking possible actions with possible outcomes. After reviewing some recent developments centering on the common-cause counterexamples to the standard approach, I introduce and briefly discuss the key notions in my own approach. (This approach has essentially the same results as the causal (...) approach in common-cause cases.) I then discuss the Rule of Dominance and find, in the context of the present proposal, that it cannot serve as an independent source of action justification. Turning next to Newcomb''s Problem, I argue that the much discussed issue of back-tracking counterfactuals is something of a red herring for decision theory. Once the twin distractions of back-tracking counterfactuals and Dominance Reasoning are set aside the 1-box solution emerges as a natural consequence of the present proposal. It is of interest that this proposal agrees with the causal approach in the standard common-cause examples and the expected-utility approach in the Newcomb case: one can be smart and rich and keep on smoking. (shrink)

Causal eliminativists maintain that all causal talk is false. The prospects for such a view seem to be stymied by an indispensability argument, charging that any agent must distinguish between effective and ineffective strategies, and that such a distinction must commit that agent to causal notions. However, this argument has been under-explored. The contributions of this paper are twofold: first, I provide a thorough explication of the indispensability argument and the various ways it might be defended. Second, I point to (...) an important limitation in the argument and suggest that it does not give us sufficient reason to reject eliminativism. In support of this last claim, I show that the distinction between effective and ineffective strategies could perfectly well be grounded in a counterfactual rather than a causal decision theory and argue that there are fully adequate explanations of how we could come to make the requisite counterfactual judgments that need not invoke causal concepts. (shrink)

Quine and others have recommended principles of charity which discourage judgments of irrationality. Such principles have been proposed to govern translation, psychology, and economics. After comparing principles of charity of different degrees of severity, we argue that the stronger principles are likely to block understanding of human behavior and impede progress toward improving it. We support a moderate principle of charity which leaves room for empirically justified judgments of irrationality.

Examples involving common causes — most prominently, examples involving genetically influenced choices — are analytically equivalent not to standard Newcomb Problems — in which the Predictor genuinely predicts the agent's decision — but to non-standard Newcomb Problems — in which the Predictor guarantees the truth of her predictions by interfering with the agent's decision to make the agent choose as it was predicted she would. When properly qualified, causal and epistemic decision theories diverge only on standard — not on non-standard (...) — Newcomb Problems, and thus not on examples involving common causes. (shrink)

Jim Joyce has argued that David Lewis’s formulation of causal decision theory is inadequate because it fails to apply to the “small world” decisions that people face in real life. Meanwhile, several authors have argued that causal decision theory should be developed such that it integrates the interventionist approach to causal modeling because of the expressive power afforded by the language of causal models, but, as of now, there has been little work towards this end. In this paper, I propose (...) a variant of Lewis’s causal decision theory that is intended to meet both of these demands. Specifically, I argue that Lewis’s causal decision theory can be rendered applicable to small world decisions if one analyzes his dependency hypotheses as causal hypotheses that depend on the interventionist causal modeling framework for their semantics. I then argue that this interventionist variant of Lewis’s causal decision theory is preferable to interventionist causal decision theories that purportedly generalize Lewis’s through the use of conditional probabilities. This is because Lewisian interventionist decision theory captures the causal decision theorist’s conviction that any correlation between what the agent does and cannot cause should be irrelevant to the agent’s choice, while purported generalizations do not. (shrink)