Decision Theory Edited by Rachael Briggs (University of Sydney)

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  1. Simon Burgess (2012). Newcomb's Problem and its Conditional Evidence: A Common Cause of Confusion. Synthese 184 (3):319-339.
    This paper aims to make three contributions to decision theory. First there is the hope that it will help to re-establish the legitimacy of the problem, pace various recent analyses provided by Maitzen and Wilson, Slezak and Priest. Second, after pointing out that analyses of the problem have generally relied upon evidence that is conditional on the taking of one particular option, this paper argues that certain assumptions implicit in those analyses are subtly flawed. As a third contribution, the piece (...)
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  2. Paul Weirich (2004). Realistic Decision Theory: Rules for Nonideal Agents in Nonideal Circumstances. OUP USA.
    Within traditional decision theory, common decision principles - e.g. the principle to maximize utility -- generally invoke idealization; they govern ideal agents in ideal circumstances. In Realistic Decision Theory, Paul Weirch adds practicality to decision theory by formulating principles applying to nonideal agents in nonideal circumstances, such as real people coping with complex decisions. Bridging the gap between normative demands and psychological resources, Realistic Decision Theory is essential reading for theorists seeking precise normative decision principles that acknowledge the limits and (...)
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Decision-Theoretic Frameworks
  1. Frank Arntzenius, No Regrets.
    I argue that standard decision theories, namely causal decision theory and evidential decision theory, are incoherent. I devise a new decision theory, from which standard game theory will follow as a corollary.
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  2. Gustaf Arrhenius & Wlodek Rabinowicz (2005). Value and Unacceptable Risk. Economics and Philosophy 21 (2):177-197.
    Consider a transitive value ordering of outcomes and lotteries on outcomes, which satisfies substitutivity of equivalents and obeys “continuity for easy cases,” i.e., allows compensating risks of small losses by chances of small improvements. Temkin (2001) has argued that such an ordering must also – rather counter-intuitively – allow chances of small improvements to compensate risks of huge losses. In this paper, we show that Temkin's argument is flawed but that a better proof is possible. However, it is more difficult (...)
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  3. Magnus Boman (1999). Norms in Artificial Decision Making. Artificial Intelligence and Law 7 (1).
    A method for forcing norms onto individual agents in a multi-agent system is presented. The agents under study are supersoft agents: autonomous artificial agents programmed to represent and evaluate vague and imprecise information. Agents are further assumed to act in accordance with advice obtained from a normative decision module, with which they can communicate. Norms act as global constraints on the evaluations performed in the decision module and hence no action that violates a norm will be suggested to any agent. (...)
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  4. Franz Dietrich, How to Reach Legitimate Decisions When the Procedure is Controversial.
    Imagine a group that faces a decision problem but does not agree on which decision procedure is appropriate. In that case, can a decision be reached that respects the procedural concerns of the group? There is a sense in which legitimate decisions are possible even if people disagree on which procedure to use. I propose to decide in favour of an option which maximizes the number of persons whose judged-right procedure happens to entail this decision given the profile. This decision (...)
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  5. Alan Hájek & Harris Nover (2006). Perplexing Expectations. Mind 115 (459):703 - 720.
    This paper revisits the Pasadena game (Nover and Háyek 2004), a St Petersburg-like game whose expectation is undefined. We discuss serveral respects in which the Pasadena game is even more troublesome for decision theory than the St Petersburg game. Colyvan (2006) argues that the decision problem of whether or not to play the Pasadena game is ‘ill-posed’. He goes on to advocate a ‘pluralism’ regarding decision rules, which embraces dominance reasoning as well as maximizing expected utility. We rebut Colyvan’s argument, (...)
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  6. Howard Margolis (2000). Simple Heuristics That Make Us Dumb. Behavioral and Brain Sciences 23 (5):758-758.
    The simple heuristics that may indeed usually make us smart–or at least smart enough–in contexts of individual choice will sometimes make us dumb, especially in contexts of social choice. Here each individual choice (or vote) has little impact on the overall choice, although the overall choice is compounded out of the individual choices. I use an example (risk aversion) to illustrate the point.
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  7. Alastair Norcross (1998). Great Harms From Small Benefits Grow: How Death Can Be Outweighed by Headaches. Analysis 58 (2):152–158.
    Suppose that a very large number of people, say one billion, will suffer a moderately severe headache for the next twenty-four hours. For these billion people, the next twenty-four hours will be fairly unpleasant, though by no means unbearable. However, there will be no side-effects from these headaches; no drop in productivity in the work-place, no lapses in concentration leading to accidents, no unkind words spoken to loved ones that will later fester. Nonetheless, it is clearly desirable that these billion (...)
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Causal Decision Theory
  1. Arif Ahmed, Causal Decision Theory is False.
    Causal Decision Theory (CDT) cares only about the effects of a contemplated act, not its causes. The paper 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.
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  2. Arif Ahmed, Smokers and Psychos: Egan Cases Don't Work.
    Andy Egan's Smoking Lesion and Psycho Button cases are supposed to be counterexamples to Causal Decision Theory. This paper argues that they are not: more precisely, it argues that if CDT makes the right call in Newcomb's problem then it makes the right call in Egan cases too.
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  3. Arif Ahmed & Huw Price (forthcoming). Arntzenius on 'Why Ain'cha Rich?'. Erkenntnis:-.
    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 (...)
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  4. M. Albert (2007). The Propensity Theory: A Decision-Theoretic Restatement. Synthese 156 (3):587 - 603.
    Probability theory is important because of its relevance for decision making, which also means: its relevance for the single case. The propensity theory of objective probability, which addresses the single case, is subject to two problems: Humphreys’ problem of inverse probabilities and the problem of the reference class. The paper solves both problems by restating the propensity theory using (an objectivist version of) Pearl’s approach to causality and probability, and by applying a decision-theoretic perspective. Contrary to a widely held view, (...)
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  5. Brad Armendt (1988). Impartiality and Causal Decision Theory. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:326 - 336.
    Defenders of sophisticated evidential decision theory (EDT) have argued (1) that its failure to provide correct recommendations in problems where the agent believes himself asymmetrically fallible in executing his choices is no flaw of the theory, and (2) that causal decision theory gives incorrect recommendations in certain examples unless it is supplemented with an additional metatickle or ratifiability deliberation mechanism. In the first part of this paper, I argue that both positions are incorrect. In the second part of the paper, (...)
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  6. Brad Armendt (1986). A Foundation for Causal Decision Theory. Topoi 5 (1):3-19.
    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 (...)
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  7. Richard Bradley (2001). Foundations of Causal Decision Theory, James M. Joyce. Cambridge University Press, 1999, XII + 268 Pages. Economics and Philosophy 17 (2):275-294.
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  8. Richard Bradley (2001). Review. James M. Joyce 'Foundations of Causal Decision Theory' [Book Review]. Economics and Philosophy 17 (2):275-294.
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  9. John Cantwell (2010). On an Alleged Counter-Example to Causal Decision Theory. Synthese 173 (2).
    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 (acts that once decided (...)
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  10. Eric G. Cavalcanti (2010). Causation, Decision Theory, and Bell's Theorem: A Quantum Analogue of the Newcomb Problem. British Journal for the Philosophy of Science 61 (3):569-597.
    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 (...)
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  11. John Collins, Supposition and Choice: Why 'Causal Decision Theory' is a Misnomer.
    This paper has as its topic two recent philosophical disputes. One of these disputes is internal to the project known as decision theory, and while by now familiar to many, may well seem to be of pressing concern only to specialists. It has been carried on over the last twenty years or so, but by now the two opposing camps are pretty well entrenched in their respective positions, and the situation appears to many observers (as well as to some of (...)
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  12. Daniel Dohrn, DeRose on the Conditionals of Deliberation.
    I take issue with two claims of DeRose: Conditionals of deliberation must not depend on backtracking grounds. ‘Were’ed-up conditionals coincide with future-directed indicative conditionals; the only difference in their meaning is that they must not depend on backtracking grounds. I use Egan’s counterexamples to causal decision theory to contest the first and an example of backtracking reasoning by David Lewis to contest the second claim. I tentatively outline a rivaling account of ‘were’ed-up conditionals which combines features of the standard analysis (...)
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  13. Dorothy Edgington (2011). Conditionals, Causation, and Decision. Analytic Philosophy 52 (2):75-87.
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  14. Ellery Eells (2000). James M. Joyce the Foundations of Causal Decision Theory. British Journal for the Philosophy of Science 51 (4):893-900.
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  15. Ellery Eells (1984). Causal Decision Theory. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1984:177 - 200.
    After a brief presentation of evidential decision theory, causal decision theory, and Newcomb type prima facie counterexamples to the evidential theory, three kinds of "metatickle" defenses of the evidential theory are discussed. Each has its weaknesses, but one of them seems stronger than the other two. The weaknesses of the best of the three, and the intricacy of metatickle analysis, does not constitute an advantage of causal decision theory over the evidential theory, however. It is argued, by way of an (...)
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  16. Andy Egan (2007). Some Counterexamples to Causal Decision Theory. Philosophical Review 116 (1):93-114.
    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 (...)
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  17. Justin C. Fisher, Disposition-Based Decision Theory.
    I develop and defend a version of what I call Disposition-Based Decision Theory (or DBDT). I point out important problems in David Gauthier’s (1985, 1986) formulation of DBDT, and carefully develop a more defensible formulation. I then compare my version of DBDT to the currently most widely accepted decision theory, Causal Decision Theory (CDT). Traditional intuition-based arguments fail to give us any strong reason to prefer either theory over the other, but I propose an alternative strategy for resolving this debate. (...)
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  18. Branden Fitelson (2003). Review: The Foundations of Causal Decision Theory. Mind 112 (447):545-551.
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  19. Johan E. Gustafsson (2011). A Note in Defence of Ratificationism. Erkenntnis 75 (1):147–150.
    Andy Egan argues that neither evidential nor causal decision theory gives the intuitively right recommendation in the cases The Smoking Lesion, The Psychopath Button, and The Three-Option Smoking Lesion. Furthermore, Egan argues that we cannot avoid these problems by any kind of ratificationism. This paper develops a new version of ratificationism that gives the right recommendations. Thus, the new proposal has an advantage over evidential and casual decision theory and standard ratificationist evidential decision theory.
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  20. William Harper (1988). Decisions, Games and Equilibrium Solutions. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:344 - 362.
    This paper includes a survey of decision theories directed toward exploring the adequacy of alternative approaches for application to game theoretic reasoning, a review of the classic results of von Neumann and Morgenstern and Nash about equilibrium solutions, an account of a recent challenge to the idea that solutions should be equilibria, and, finally, an explicit reconstruction and defense (using the resources of causal decision theory) of the classic indirect argument for equilibrium solutions.
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  21. William Harper (1986). Mixed Strategies and Ratifiability in Causal Decision Theory. Erkenntnis 24 (1):25 - 36.
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  22. William Harper (1984). Ratifiability and Causal Decision Theory: Comments on Eells and Seidenfeld. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1984:213 - 228.
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  23. Christopher Read Hitchcock (1996). Causal Decision Theory and Decision-Theoretic Causation. Noûs 30 (4):508-526.
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  24. Daniel Hunter & Reed Richter (1978). Counterfactuals and Newcomb's Paradox. Synthese 39 (2):249 - 261.
    In their development of causal decision theory, Allan Gibbard and William Harper advocate a particular method for calculating the expected utility of an action, a method based upon the probabilities of certain counterfactuals. Gibbard and Harper then employ their method to support a two-box solution to Newcomb’s paradox. This paper argues against some of Gibbard and Harper’s key claims concerning the truth-values and probabilities of counterfactuals involved in expected utility calculations, thereby disputing their analysis of Newcomb’s Paradox. If we are (...)
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  25. M. Janusz (2001). The Foundations of Causal Decision Theory. Philosophical Review 110 (2):296-300.
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  26. Richard Jeffrey (1981). The Logic of Decision Defended. Synthese 48 (3):473 - 492.
    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.
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  27. James Joyce (1999). The Foundations of Causal Decision Theory. Cambridge University Press.
    The most complete defense of causal decision theory available.
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  28. James M. Joyce (2002). Levi on Causal Decision Theory and the Possibility of Predicting One's Own Actions. Philosophical Studies 110 (1):69 - 102.
    Isaac Levi has long criticized causal decisiontheory on the grounds that it requiresdeliberating agents to make predictions abouttheir own actions. A rational agent cannot, heclaims, see herself as free to choose an actwhile simultaneously making a prediction abouther likelihood of performing it. Levi is wrongon both points. First, nothing in causaldecision theory forces agents to makepredictions about their own acts. Second,Levi's arguments for the ``deliberation crowdsout prediction thesis'' rely on a flawed modelof the measurement of belief. Moreover, theability of agents (...)
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  29. James M. Joyce (2000). Why We Still Need the Logic of Decision. Philosophy of Science 67 (3):13.
    In The Logic of Decision Richard Jeffrey defends a version of expected utility theory that advises agents to choose acts with an eye to securing evidence for thinking that desirable results will ensue. Proponents of "causal" decision theory have argued that Jeffrey's account is inadequate because it fails to properly discriminate the causal features of acts from their merely evidential properties. Jeffrey's approach has also been criticized on the grounds that it makes it impossible to extract a unique probability/utility representation (...)
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  30. David Lewis (1983). Levi Against U-Maximization. Journal of Philosophy 80 (9):531-534.
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  31. David Lewis (1981). Causal Decision Theory. Australasian Journal of Philosophy 59 (1):5 – 30.
    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.
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  32. Patrick Maher (1990). Symptomatic Acts and the Value of Evidence in Causal Decision Theory. Philosophy of Science 57 (3):479-498.
    A "symptomatic act" is an act that is evidence for a state that it has no tendency to cause. In this paper I show that when the evidential value of a symptomatic act might influence subsequent choices, causal decision theory may initially recommend against its own use for those subsequent choices. And if one knows that one will nevertheless use causal decision theory to make those subsequent choices, causal decision theory may favor the one-box solution in Newcomb's problem, and may (...)
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  33. Christopher J. G. Meacham (2010). Binding and its Consequences. Philosophical Studies 149 (1):49-71.
    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 (...)
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  34. John L. Pollock (2002). Causal Probability. Synthese 132 (1-2):143 - 185.
    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.
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  35. Huw Price (1986). Against Causal Decision Theory. Synthese 67 (2):195 - 212.
    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 (...)
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  36. Piers Rawling (1993). Choice and Conditional Expected Utility. Synthese 94 (2):303 - 328.
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  37. Reed Richter (1984). Rationality Revisited. Australasian Journal of Philosophy 62 (4):392 – 403.
    This paper looks at a dispute decision theory about how best to characterize expected utility maximization and express the logic of rational choice. Where A1, … , An are actions open to some particular agent, and S1, … , Sn are mutually exclusive states of the world such that the agent knows at least one of which obtains, does the logic of rational choice require an agent to consider the conditional probability of choice Ai given that some state Si obtains, (...)
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  38. David Schmidtz & Sarah Wright (2004). What Nozick Did for Decision Theory. Midwest Studies in Philosophy 28 (1):282–294.
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  39. Teddy Seidenfeld (1984). Comments on Causal Decision Theory. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1984:201 - 212.
    PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, Vol. 1984, Volume Two: Symposia and Invited Papers. (1984), pp. 201-212.
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  40. Michael J. Shaffer (2009). Decision Theory, Intelligent Planning and Counterfactuals. Minds and Machines 19 (1):61-92.
    The ontology of decision theory has been subject to considerable debate in the past, and discussion of just how we ought to view decision problems has revealed more than one interesting problem, as well as suggested some novel modifications of classical decision theory. In this paper it will be argued that Bayesian, or evidential, decision-theoretic characterizations of decision situations fail to adequately account for knowledge concerning the causal connections between acts, states, and outcomes in decision situations, and so they are (...)
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  41. Brian Skyrms (1985). Ultimate and Proximate Consequences in Causal Decision Theory. Philosophy of Science 52 (4):608-611.
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  42. Brian Skyrms (1982). Causal Decision Theory. Journal of Philosophy 79 (11):695-711.
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  43. Peter Slezak, Demons, Decievers and Liars: Newcomb’s Malin Génie.
    A fully adequate solution to Newcomb’s Problem (Nozick 1969) should reveal the source of its extraordinary elusiveness and persis- tent intractability. Recently, a few accounts have independently sought to meet this criterion of adequacy by exposing the underlying source of the problem’s profound puzzlement. Thus, Sorensen (1987), Slezak (1998), Priest (2002) and Maitzen and Wilson (2003) share the ‘no box’ view according to which the very idea that there is a right choice is mis- conceived since the problem is ill-formed (...)
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  44. Jordan Howard Sobel (1989). Partition-Theorems for Causal Decision Theories. Philosophy of Science 56 (1):70-93.
    Two partition-theorems are proved for a particular causal decision theory. One is restricted to a certain kind of partition of circumstances, and analyzes the utility of an option in terms of its utilities in conjunction with circumstances in this partition. The other analyzes an option's utility in terms of its utilities conditional on circumstances and is quite unrestricted. While the first form seems more useful for applications, the second form may be of theoretical importance in foundational exercises. Comparisons are made (...)
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  45. Jordan Howard Sobel (1986). Notes on Decision Theory: Old Wine in New Bottles. Australasian Journal of Philosophy 64 (4):407 – 437.
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  46. Jordan Howard Sobel (1985). Circumstances and Dominance in a Causal Decision Theory. Synthese 63 (2):167 - 202.
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  47. Wolfgang Spohn (forthcoming). Reversing 30 Years of Discussion: Why Causal Decision Theorists Should One-Box. Synthese:-.
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  48. Eric Swanson (forthcoming). Conditional Excluded Middle Without the Limit Assumption. Philosophy and Phenomenological Research:no-no.
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  49. David Wallace (2010). Diachronic Rationality and Prediction-Based Games. Proceedings of the Aristotelian Society 110 (3pt3):243-266.
    I explore the debate about causal versus evidential decision theory, and its recent developments in the work of Andy Egan, through the method of some simple games based on agents' predictions of each other's actions. My main focus is on the requirement for rational agents to act in a way which is consistent over time and its implications for such games and their more realistic cousins.
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  50. Ralph Wedgwood (2011). Gandalf's Solution to the Newcomb Problem. Synthese:1-33.
    ‘I wish it need not have happened in my time’, said Frodo. ‘So do I,’ said Gandalf, ‘and so do all who live to see such times. But that is not for them to decide. All we have to decide is what to do with the time that is given us.’.
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  51. Paul Weirich, Causal Decision Theory. Stanford Encyclopedia of Philosophy.
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  52. Paul Weirich (1988). Hierarchical Maximization of Two Kinds of Expected Utility. Philosophy of Science 55 (4):560-582.
    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 (...)
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  53. Paul Weirich (1986). Decisions in Dynamic Settings. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:438 - 449.
    In a decision problem with a dynamic setting there is at least one option whose realization would change the expected utilities of options by changing the probability or utility function with respect to which the expected utilities of options are computed. A familiar example is Newcomb's problem. William Harper proposes a generalization of causal decision theory intended to cover all decision problems with dynamic settings, not just Newcomb's problem. His generalization uses Richard Jeffrey's ideas on ratifiability, and material from game (...)
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Evidential Decision Theory
  1. Arif Ahmed, Smokers and Psychos: Egan Cases Don't Work.
    Andy Egan's Smoking Lesion and Psycho Button cases are supposed to be counterexamples to Causal Decision Theory. This paper argues that they are not: more precisely, it argues that if CDT makes the right call in Newcomb's problem then it makes the right call in Egan cases too.
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  2. Arif Ahmed (2005). Evidential Decision Theory and Medical Newcomb Problems. British Journal for the Philosophy of Science 56 (2):191-198.
    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.
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  3. Helen Beebee, Peter Menzies & Christopher Hitchcock (2009). The Oxford Handbook of Causation. Oxford University Press.
    Causation is a central topic in many areas of philosophy, including metaphysics, epistemology, philosophy of mind, ethics, history of philosophy, and philosophy ...
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  4. Ethan D. Bolker (2000). An Existence Theorem for the Logic of Decision. Philosophy of Science 67 (3):17.
    In this paper I discuss some of the mathematics behind an often quoted existence theorem from Richard Jeffrey's The Logic of Decision (Jeffrey 1990) in order to pose several new questions about the meaning and value of that mathematics for decision theory.
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  5. Dorothy Edgington (2011). Conditionals, Causation, and Decision. Analytic Philosophy 52 (2):75-87.
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  6. Ellery Eells (1989). The Popcorn Problem: Sobel on Evidential Decision Theory and Deliberation-Probability Dynamics. Synthese 81 (1):9 - 20.
    I defend evidential decision theory and the theory of deliberation-probability dynamics from a recent criticism advanced by Jordan Howard Sobel. I argue that his alleged counterexample to the theories, called the Popcorn Problem is not a genuine counterexample.
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  7. Ellery Eells & Elliott Sober (1986). Common Causes and Decision Theory. Philosophy of Science 53 (2):223-245.
    One of us (Eells 1982) has defended traditional evidential decision theory against prima facie Newcomb counterexamples by assuming that a common cause forms a conjunctive fork with its joint effects. In this paper, the evidential theory is defended without this assumption. The suggested rationale shows that the theory's assumptions are not about the nature of causality, but about the nature of rational deliberation. These presuppositions are weak enough for the argument to count as a strong justification of the evidential theory.
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  8. James Franklin, Mark Burgman, Scott Sisson & J. K. Martin (2008). Evaluating Extreme Risks in Invasion Ecology: Learning From Banking Compliance. Diversity and Distributions 14:581-591.
    methods that have shown promise for improving extreme risk analysis, particularly for assessing the risks of invasive pests and pathogens associated with international trade. We describe the legally inspired regulatory regime for banks, where these methods have been brought to bear on extreme ‘operational risks’. We argue that an ‘advocacy model’ similar to that used in the Basel II compliance regime for bank operational risks and to a lesser extent in biosecurity import risk analyses is ideal for permitting the diversity (...)
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  9. Johan E. Gustafsson (2011). A Note in Defence of Ratificationism. Erkenntnis 75 (1):147–150.
    Andy Egan argues that neither evidential nor causal decision theory gives the intuitively right recommendation in the cases The Smoking Lesion, The Psychopath Button, and The Three-Option Smoking Lesion. Furthermore, Egan argues that we cannot avoid these problems by any kind of ratificationism. This paper develops a new version of ratificationism that gives the right recommendations. Thus, the new proposal has an advantage over evidential and casual decision theory and standard ratificationist evidential decision theory.
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  10. Daniel Hunter & Reed Richter (1978). Counterfactuals and Newcomb's Paradox. Synthese 39 (2):249 - 261.
    In their development of causal decision theory, Allan Gibbard and William Harper advocate a particular method for calculating the expected utility of an action, a method based upon the probabilities of certain counterfactuals. Gibbard and Harper then employ their method to support a two-box solution to Newcomb’s paradox. This paper argues against some of Gibbard and Harper’s key claims concerning the truth-values and probabilities of counterfactuals involved in expected utility calculations, thereby disputing their analysis of Newcomb’s Paradox. If we are (...)
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  11. Frank Jackson & Robert Pargetter (1983). Where the Tickle Defence Goes Wrong. Australasian Journal of Philosophy 61 (3):295 – 299.
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  12. Richard Jeffrey (1992). Probability Kinematics and Causality. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1992:365 - 373.
    Making up your mind can include making up your mind about how to change your mind. Here a suggestion for coding imputations of influence into the kinematics of judgmental probabilities is applied to the treatment of Newcomb problems in The Logic of Decision framework. The suggestion is that what identifies you as treating judgmental probabilistic covariance of X and Y as measuring an influence of X on Y is constancy of your probabilities for values of Y conditionally on values of (...)
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  13. Richard Jeffrey (1983). The Logic of Decision. University of Chicago Press.
    "Frederic Schick, Journal of Philosophy This book uses elementary logical and mathematical means to philosophical end: elucidation of the notions of subjective ...
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  14. Richard Jeffrey (1981). The Logic of Decision Defended. Synthese 48 (3):473 - 492.
    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.
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  15. James M. Joyce (2000). Why We Still Need the Logic of Decision. Philosophy of Science 67 (3):13.
    In The Logic of Decision Richard Jeffrey defends a version of expected utility theory that advises agents to choose acts with an eye to securing evidence for thinking that desirable results will ensue. Proponents of "causal" decision theory have argued that Jeffrey's account is inadequate because it fails to properly discriminate the causal features of acts from their merely evidential properties. Jeffrey's approach has also been criticized on the grounds that it makes it impossible to extract a unique probability/utility representation (...)
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  16. Phyllis Kirstin McKay (2007). Freedom, Fiction and Evidential Decision Theory. Erkenntnis 66 (3):393 - 407.
    This paper argues against evidential decision-theory, by showing that the newest responses to its biggest current problem – the medical Newcomb problems – don’t work. The latest approach is described, and the arguments of two main proponents of it – Huw Price and CR Hitchcock – clearly distinguished and examined. It is argued that since neither new defence is successful, causation remains essential to understanding means-end agency.
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  17. Christopher J. G. Meacham (2010). Binding and its Consequences. Philosophical Studies 149 (1):49-71.
    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 (...)
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  18. Huw Price (1991). Agency and Probabilistic Causality. British Journal for the Philosophy of Science 42 (2):157-176.
    Probabilistic accounts of causality have long had trouble with ‘spurious’ evidential correlations. Such correlations are also central to the case for causal decision theory—the argument that evidential decision theory is inadequate to cope with certain sorts of decision problem. However, there are now several strong defences of the evidential theory. Here I present what I regard as the best defence, and apply it to the probabilistic approach to causality. I argue that provided a probabilistic theory appeals to the notions of (...)
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  19. Huw Price (1986). Against Causal Decision Theory. Synthese 67 (2):195 - 212.
    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 (...)
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  20. Huw Price & Brad Weslake (2009). The Time-Asymmetry of Causation. In Helen Beebee, Peter Menzies & Christopher Hitchcock (eds.), The Oxford Handbook of Causation. Oxford University Press.
    One of the most striking features of causation is that causes typically precede their effects – the causal arrow is strongly aligned with the temporal arrow. Why should this be so? We offer an opinionated guide to this problem, and to the solutions currently on offer. We conclude that the most promising strategy is to begin with the de facto asymmetry of human deliberation, characterised in epistemic terms, and to build out from there. More than any rival, this subjectivist approach (...)
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  21. Nicholas Rescher & Alan Ross Anderson (1966). The Logic of Decision and Action. Pittsburgh]University of Pittsburgh Press.
    The four main essays in this volume investigate new sectors of the theory of decision, preference, act-characteristics, and action analysis.
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  22. Reed Richter (1984). Rationality Revisited. Australasian Journal of Philosophy 62 (4):392 – 403.
    This paper looks at a dispute decision theory about how best to characterize expected utility maximization and express the logic of rational choice. Where A1, … , An are actions open to some particular agent, and S1, … , Sn are mutually exclusive states of the world such that the agent knows at least one of which obtains, does the logic of rational choice require an agent to consider the conditional probability of choice Ai given that some state Si obtains, (...)
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  23. Michael J. Shaffer (2009). Decision Theory, Intelligent Planning and Counterfactuals. Minds and Machines 19 (1):61-92.
    The ontology of decision theory has been subject to considerable debate in the past, and discussion of just how we ought to view decision problems has revealed more than one interesting problem, as well as suggested some novel modifications of classical decision theory. In this paper it will be argued that Bayesian, or evidential, decision-theoretic characterizations of decision situations fail to adequately account for knowledge concerning the causal connections between acts, states, and outcomes in decision situations, and so they are (...)
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  24. David Shaw & David Conway (2010). Pascal’s Wager, Infective Endocarditis and the “No-Lose” Philosophy in Medicine. Heart 96 (1):15-18.
    Doctors and dentists have traditionally used antibiotic prophylaxis in certain patient groups in order to prevent infective endocarditis (IE). New guidelines, however, suggest that the risk to patients from using antibiotics is higher than the risk from IE. This paper analyses the relative risks of prescribing and not prescribing antibiotic prophylaxis against the background of Pascal’s Wager, the infamous assertion that it is better to believe in God regardless of evidence, because of the prospective benefits should He exist. Many doctors (...)
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  25. Peter Slezak, Demons, Decievers and Liars: Newcomb’s Malin Génie.
    A fully adequate solution to Newcomb’s Problem (Nozick 1969) should reveal the source of its extraordinary elusiveness and persis- tent intractability. Recently, a few accounts have independently sought to meet this criterion of adequacy by exposing the underlying source of the problem’s profound puzzlement. Thus, Sorensen (1987), Slezak (1998), Priest (2002) and Maitzen and Wilson (2003) share the ‘no box’ view according to which the very idea that there is a right choice is mis- conceived since the problem is ill-formed (...)
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  26. Jordan Howard Sobel (1988). Defenses and Conservative Revisions of Evidential Decision Theories: Metatickles and Ratificationism. Synthese 75 (1):107 - 131.
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  27. Jordan Howard Sobel (1986). Notes on Decision Theory: Old Wine in New Bottles. Australasian Journal of Philosophy 64 (4):407 – 437.
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  28. Carl Wagner, Jeffrey Conditioning and External Bayesianity.
    Abstract. Suppose that several individuals who have separately assessed prior probability distributions over a set of possible states of the world wish to pool their individual distributions into a single group distribution, while taking into account jointly perceived new evidence. They have the option of (i) first updating their individual priors and then pooling the resulting posteriors or (ii) first pooling their priors and then updating the resulting group prior. If the pooling method that they employ is such that they (...)
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  29. David Wallace (2010). Diachronic Rationality and Prediction-Based Games. Proceedings of the Aristotelian Society 110 (3pt3):243-266.
    I explore the debate about causal versus evidential decision theory, and its recent developments in the work of Andy Egan, through the method of some simple games based on agents' predictions of each other's actions. My main focus is on the requirement for rational agents to act in a way which is consistent over time and its implications for such games and their more realistic cousins.
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  30. Ralph Wedgwood (2011). Gandalf's Solution to the Newcomb Problem. Synthese:1-33.
    ‘I wish it need not have happened in my time’, said Frodo. ‘So do I,’ said Gandalf, ‘and so do all who live to see such times. But that is not for them to decide. All we have to decide is what to do with the time that is given us.’.
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Decision-Theoretic Frameworks, Misc
  1. Rolf Aaberge (2011). Empirical Rules of Thumb for Choice Under Uncertainty. Theory and Decision 71 (3):431-438.
    A substantial body of empirical evidence shows that individuals overweight extreme events and act in conflict with the expected utility theory. These findings were the primary motivation behind the development of a rank-dependent utility theory for choice under uncertainty. The purpose of this paper is to demonstrate that some simple empirical rules of thumb for choice under uncertainty are consistent with the rank-dependent utility theory.
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  2. Christophe Abraham & Jean-Pierre Daures (2000). Global Robustness with Respect to the Loss Function and the Prior. Theory and Decision 48 (4):359-381.
    We propose a class [I,S] of loss functions for modeling the imprecise preferences of the decision maker in Bayesian Decision Theory. This class is built upon two extreme loss functions I and S which reflect the limited information about the loss function. We give an approximation of the set of Bayes actions for every loss function in [I,S] and every prior in a mixture class; if the decision space is a subset of R, we obtain the exact set.
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  3. Arif Ahmed, Smokers and Psychos: Egan Cases Don't Work.
    Andy Egan's Smoking Lesion and Psycho Button cases are supposed to be counterexamples to Causal Decision Theory. This paper argues that they are not: more precisely, it argues that if CDT makes the right call in Newcomb's problem then it makes the right call in Egan cases too.
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  4. Alan Hájek (2006). In Memory of Richard Jeffrey: Some Reminiscences and Some Reflections onThe Logic of Decision. Philosophy of Science 73 (5):947-958.
    This paper is partly a tribute to Richard Jeffrey, partly a reflection on some of his writings, The Logic of Decision in particular. I begin with a brief biography and some fond reminiscences of Dick. I turn to some of the key tenets of his version of Bayesianism. All of these tenets are deployed in my discussion of his response to the St. Petersburg paradox, a notorious problem for decision theory that involves a game of infinite expectation. Prompted by that (...)
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  5. Frank Arntzenius (2008). No Regrets, Or: Edith Piaf Revamps Decision Theory. Erkenntnis 68 (2):277-297.
    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.
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  6. José Luis Bermúdez (forthcoming). Pitfalls for Realistic Decision Theory: An Illustration From Sequential Choice. Synthese.
    Decision theory is a theory of rationality, but the concept of rationality has several different dimensions. Making decision theory more realistic with respect to one dimension may well have the result of making it less realistic in another dimension. This paper illustrates this tension in the context of sequential choice. Trying to make decision theory more realistic by accommodating resoluteness and commitment brings the normative assessment dimension of rationality into conflict with the action-guiding dimension. In the case of resolute choice (...)
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  7. Ken Binmore, Making Decisions in Large Worlds (Pdf 141k).
    This paper argues that we need to look beyond Bayesian decision theory for an answer to the general problem of making rational decisions under uncertainty. The view that Bayesian decision theory is only genuinely valid in a small world was asserted very firmly by Leonard Savage [18] when laying down the principles of the theory in his path-breaking Foundations of Statistics. He makes the distinction between small and large worlds in a folksy way by quoting the proverbs ”Look before you (...)
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  8. Ethan D. Bolker (2000). An Existence Theorem for the Logic of Decision. Philosophy of Science 67 (3):17.
    In this paper I discuss some of the mathematics behind an often quoted existence theorem from Richard Jeffrey's The Logic of Decision (Jeffrey 1990) in order to pose several new questions about the meaning and value of that mathematics for decision theory.
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