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  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. Arif Ahmed (2010). Causation and Decision. Proceedings of the Aristotelian Society 110 (2pt2):111-131.
    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.
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  5. Mark Alfano (2012). Wilde Heuristics and Rum Tum Tuggers: Preference Indeterminacy and Instability. Synthese 189 (S1):5-15.
    Models in decision theory and game theory assume that preferences are determinate: for any pair of possible outcomes, a and b, an agent either prefers a to b, prefers b to a, or is indifferent as between a and b. Preferences are also assumed to be stable: provided the agent is fully informed, trivial situational influences will not shift the order of her preferences. Research by behavioral economists suggests, however, that economic and hedonic preferences are to some degree indeterminate and (...)
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  6. Frank Arntzenius (2008). No Regrets, Or: Edith Piaf Revamps Decision Theory. [REVIEW] 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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  7. Adam Bales, Daniel Cohen & Toby Handfield (2014). Decision Theory for Agents with Incomplete Preferences. Australasian Journal of Philosophy 92 (3):453-70.
    (2014). Decision Theory for Agents with Incomplete Preferences. Australasian Journal of Philosophy: Vol. 92, No. 3, pp. 453-470. doi: 10.1080/00048402.2013.843576.
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  8. José Luis Bermúdez (2010). Pitfalls for Realistic Decision Theory: An Illustration From Sequential Choice. Synthese 176 (1):23 - 40.
    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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  9. 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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  10. 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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  11. Darren Bradley (2013). Decision Theory, Philosophical Perspectives. In Hal Pashler (ed.), Encyclopedia of the Mind. Sage.
    Decision theory is concerned with how agents should act when the consequences of their actions are uncertain. The central principle of contemporary decision theory is that the rational choice is the choice that maximizes subjective expected utility. This entry explains what this means, and discusses the philosophical motivations and consequences of the theory. The entry will consider some of the main problems and paradoxes that decision theory faces, and some of responses that can be given. Finally the entry will briefly (...)
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  12. Richard Bradley (2007). A Unified Bayesian Decision Theory. Theory and Decision 63 (3):233-263,.
    This paper provides new foundations for Bayesian Decision Theory based on a representation theorem for preferences defined on a set of prospects containing both factual and conditional possibilities. This use of a rich set of prospects not only provides a framework within which the main theoretical claims of Savage, Ramsey, Jeffrey and others can be stated and compared, but also allows for the postulation of an extended Bayesian model of rational belief and desire from which they can be derived as (...)
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  13. Richard Bradley (1999). Conditional Desirability. Theory and Decision 47 (1):23-55.
    Conditional attitudes are not the attitudes an agent is disposed to acquire in event of learning that a condition holds. Rather they are the components of agent's current attitudes that derive from the consideration they give to the possibility that the condition is true. Jeffrey's decision theory can be extended to include quantitative representation of the strength of these components. A conditional desirability measure for degrees of conditional desire is proposed and shown to imply that an agent's degrees of conditional (...)
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  14. Richard Bradley (1998). A Representation Theorem for a Decision Theory with Conditionals. Synthese 116 (2):187-229.
    This paper investigates the role of conditionals in hypothetical reasoning and rational decision making. Its main result is a proof of a representation theorem for preferences defined on sets of sentences (and, in particular, conditional sentences), where an agent’s preference for one sentence over another is understood to be a preference for receiving the news conveyed by the former. The theorem shows that a rational preference ordering of conditional sentences determines probability and desirability representations of the agent’s degrees of belief (...)
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  15. Rachael Briggs (2010). Decision-Theoretic Paradoxes as Voting Paradoxes. Philosophical Review 119 (1):1-30.
    It is a platitude among decision theorists that agents should choose their actions so as to maximize expected value. But exactly how to define expected value is contentious. Evidential decision theory (henceforth EDT), causal decision theory (henceforth CDT), and a theory proposed by Ralph Wedgwood that this essay will call benchmark theory (BT) all advise agents to maximize different types of expected value. Consequently, their verdicts sometimes conflict. In certain famous cases of conflict—medical Newcomb problems—CDT and BT seem to get (...)
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  16. Berit Brogaard (1999). A Peircean Theory of Decision. Synthese 118 (3):383-401.
    It is sometimes argued that the fact that possession of perfect knowledge about the future is impossible, means that it is impossible for decisions to be rational. This reasoning is fallacious. If rationality is given a new interpretation, then decisions can be considered rational. A theory of decision that has as its basis Peirce’s theory of abduction can provide a new way of understanding decisions as rational processes. The Peircean theory of decision (i) considers decisions as part of a complete (...)
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  17. Lara Buchak (forthcoming). Decision Theory. In Christopher Hitchcock & Alan Hajek (eds.), Oxford Handbook of Probability and Philosophy. Oxford University Press.
  18. Lara Buchak (forthcoming). Risk and Tradeoffs. Erkenntnis:1-27.
    The orthodox theory of instrumental rationality, expected utility (EU) theory, severely restricts the way in which risk-considerations can figure into a rational individual's preferences. It is argued here that this is because EU theory neglects an important component of instrumental rationality. This paper presents a more general theory of decision-making, risk-weighted expected utility (REU) theory, of which expected utility maximization is a special case. According to REU theory, the weight that each outcome gets in decision-making is not the subjective probability (...)
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  19. Lara Buchak (2010). Instrumental Rationality, Epistemic Rationality, and Evidence-Gathering. Philosophical Perspectives 24 (1):85-120.
  20. John W. Carroll (1998). Book Review:Decision Theory as Philosophy Mark Kaplan. [REVIEW] Philosophy of Science 65 (4):727-.
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  21. Jake Chandler (2014). Subjective Probabilities Need Not Be Sharp. Erkenntnis 79 (6):1273-1286.
    It is well known that classical, aka ‘sharp’, Bayesian decision theory, which models belief states as single probability functions, faces a number of serious difficulties with respect to its handling of agnosticism. These difficulties have led to the increasing popularity of so-called ‘imprecise’ models of decision-making, which represent belief states as sets of probability functions. In a recent paper, however, Adam Elga has argued in favour of a putative normative principle of sequential choice that he claims to be borne out (...)
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  22. Clare Chua Chow & Rakesh K. Sarin (2002). Known, Unknown, and Unknowable Uncertainties. Theory and Decision 52 (2):127-138.
    In normative decision theory, the weight of an uncertain event in a decision is governed solely by the probability of the event. A large body of empirical research suggests that a single notion of probability does not accurately capture peoples' reactions to uncertainty. As early as the 1920s, Knight made the distinction between cases where probabilities are known and where probabilities are unknown. We distinguish another case –- the unknowable uncertainty –- where the missing information is unavailable to all. We (...)
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  23. Franz Dietrich & Christian List, Reason-Based Rationalization.
    We introduce a “reason-based” way of rationalizing an agent’s choice behaviour, which explains choices by specifying which properties of the options or choice context the agent cares about (the “motivationally salient properties”) and how he or she cares about these properties (the “fundamental preference relation”). Reason-based rationalizations can explain non-classical choice behaviour, including boundedly rational and sophisticated rational behaviour, and predict choices in unobserved contexts, an issue neglected in standard choice theory. We characterize the behavioural implications of different reason-based models (...)
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  24. Franz Dietrich & Christian List (2013). Where Do Preferences Come From? International Journal of Game Theory 42 (3):613-637.
    Rational choice theory analyzes how an agent can rationally act, given his or her preferences, but says little about where those preferences come from. Preferences are usually assumed to be fixed and exogenously given. Building on related work on reasons and rational choice, we describe a framework for conceptualizing preference formation and preference change. In our model, an agent's preferences are based on certain "motivationally salient" properties of the alternatives over which the preferences are held. Preferences may change as new (...)
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  25. Franz Dietrich & Christian List (2013). A Reason-Based Theory of Rational Choice. Noûs 47 (1):104-134.
    There is a surprising disconnect between formal rational choice theory and philosophical work on reasons. The one is silent on the role of reasons in rational choices, the other rarely engages with the formal models of decision problems used by social scientists. To bridge this gap, we propose a new, reason-based theory of rational choice. At its core is an account of preference formation, according to which an agent’s preferences are determined by his or her motivating reasons, together with a (...)
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  26. Franz Dietrich & Christian List (2005). The Two-Envelope Paradox: An Axiomatic Approach. Mind 114 (454):239-248.
    There has been much discussion on the two-envelope paradox. Clark and Shackel (2000) have proposed a solution to the paradox, which has been refuted by Meacham and Weisberg (2003). Surprisingly, however, the literature still contains no axiomatic justification for the claim that one should be indifferent between the two envelopes before opening one of them. According to Meacham and Weisberg, "decision theory does not rank swapping against sticking [before opening any envelope]" (p. 686). To fill this gap in the literature, (...)
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  27. Simone Duca (2011). The Suppositional Ramsey Test and Decision-Instability. Topoi (1):53-57.
    Abstract I analyse the relationship between the Ramsey Test (RT) for the acceptance of indicative conditionals and the so-called problem of decision-instability. In particular, I argue that the situations which allegedly bring about this problem are troublesome just in case the relevant conditionals are evaluated by non-suppositional versions, e.g. causal/evidential, of the test. In contrast, a suppositional RT, by highlighting the metacognitive nature of the evaluation of indicative conditionals, allows an agent to run a simulation of such evaluation, without yet (...)
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  28. Kenny Easwaran (2007). Review of F. Schick, Ambiguity and Logic. [REVIEW] Mind 116 (462):478-482.
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  29. Ellery Eells & William L. Harper (1991). Ratifiability, Game Theory, and the Principle of Independence of Irrelevant Alternatives. Australasian Journal of Philosophy 69 (1):1 – 19.
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  30. 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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  31. Peter Gärdenfors & Nils-Eric Sahlin (1982). Unreliable Probabilities, Risk Taking, and Decision Making. Synthese 53 (3):361-386.
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  32. Christopher Gauker (2005). The Belief-Desire Law. Facta Philosophica 7 (2):121-144.
    Many philosophers hold that for various reasons there must be psychological laws governing beliefs and desires. One of the few serious examples that they offer is the _belief-desire law_, which states, roughly, that _ceteris paribus_ people do what they believe will satisfy their desires. This paper argues that, in fact, there is no such law. In particular, decision theory does not support the contention that there is such a law.
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  33. 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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  34. Alan Hájek & Michael Smithson (2012). Rationality and Indeterminate Probabilities. Synthese 187 (1):33-48.
    We argue that indeterminate probabilities are not only rationally permissible for a Bayesian agent, but they may even be rationally required . Our first argument begins by assuming a version of interpretivism: your mental state is the set of probability and utility functions that rationalize your behavioral dispositions as well as possible. This set may consist of multiple probability functions. Then according to interpretivism, this makes it the case that your credal state is indeterminate. Our second argument begins with our (...)
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  35. Sven Ove Hansson (1996). Decision Making Under Great Uncertainty. Philosophy of the Social Sciences 26 (3):369-386.
    This article is an attempt at a systematic account of decision making under greater uncertainty than what traditional, mathematically oriented decision theory can cope with. Four components of great uncertainty are distinguished: (1) the identity of the options is not well determined (uncertainty of demarcation) ; (2) the consequences of at least some option are unknown (uncertainty of consequences); (3) it is not clear whether information obtained from others, such as experts, can be relied on (uncertainty of reliance); and (4) (...)
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  36. Sven Ove Hansson, Decision Theory.
    This text is a non-technical overview of modern decision theory. It is intended for university students with no previous acquaintance with the subject, and was primarily written for the participants of a course on risk analysis at Uppsala University in 1994.
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  37. 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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  38. Conrad Heilmann (2012). The Handbook of Rational and Social Choice: An Overview of New Foundations and Applications, Edited by Paul Anand, Prasanta K. Pattanaik and Clemens Puppe, Oxford University Press, 2009, Xi + 581 Pages. [REVIEW] Economics and Philosophy 28 (1):92-98.
    Book Reviews Conrad Heilmann, Economics and Philosophy , FirstView Article(s) .
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  39. 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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  40. Richard C. Jeffrey (1992). Probability and the Art of Judgment. Cambridge University Press.
    Richard Jeffrey is beyond dispute one of the most distinguished and influential philosophers working in the field of decision theory and the theory of knowledge. His work is distinctive in showing the interplay of epistemological concerns with probability and utility theory. Not only has he made use of standard probabilistic and decision theoretic tools to clarify concepts of evidential support and informed choice, he has also proposed significant modifications of the standard Bayesian position in order that it provide a better (...)
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  41. James M. Joyce (2010). A Defense of Imprecise Credences in Inference and Decision Making1. Philosophical Perspectives 24 (1):281-323.
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  42. 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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  43. Annemarie Kalis, Andreas Mojzisch, Sophie Schweizer & Stefan Kaiser (2008). Weakness of Will, Akrasia and the Neuropsychiatry of Decision-Making: An Interdisciplinary Perspective. Cognitive, Affective and Behavioral Neuroscience 8 (4):402-17.
    This article focuses on both daily forms of weakness of will as discussed in the philosophical debate (usually referred to as akrasia) and psychopathological phenomena as impairments of decision making. We argue that both descriptions of dysfunctional decision making can be organized within a common theoretical framework that divides the decision making process in three different stages: option generation, option selection, and action initiation. We first discuss our theoretical framework (building on existing models of decision-making stages), focusing on option generation (...)
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  44. Mark Kaplan (1983). Decision Theory as Philosophy. Philosophy of Science 50 (4):549-577.
    Is Bayesian decision theory a panacea for many of the problems in epistemology and the philosophy of science, or is it philosophical snake-oil? For years a debate had been waged amongst specialists regarding the import and legitimacy of this body of theory. Mark Kaplan had written the first accessible and non-technical book to address this controversy. Introducing a new variant on Bayesian decision theory the author offers a compelling case that, while no panacea, decision theory does in fact have the (...)
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  45. Stephen Leeds (1990). Levi's Decision Theory. Philosophy of Science 57 (1):158-168.
    Suppose my utilities are representable by a set of utility assignments, each defined for atomic sentences; suppose my beliefs are representable by a set of probability assignments. Then each of my utility assignments together with each of my probability assignments will determine a utility assignment to non-atomic sentences, in a familiar way. This paper is concerned with the question, whether I am committed to all the utility assignments so constructible. Richard Jeffrey (1984) says (in effect) "no", Isaac Levi (1974) says (...)
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  46. Isaac Levi (1982). Ignorance, Probability and Rational Choice. Synthese 53 (3):387-417.
  47. Dustin Locke, Knowledge-Free Decision Theory.
  48. Dilip B. Madan & J. C. Owings (1988). Decision Theory with Complex Uncertainties. Synthese 75 (1):25 - 44.
    A case is made for supposing that the total probability accounted for in a decision analysis is less than unity. This is done by constructing a measure on the set of all codes for computable functions in such a way that the measure of every effectively accountable subset is bounded by a number <1. The consistency of these measures with the Savage axioms for rational preference is established. Implications for applied decision theory are outlined.
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  49. Patrick Maher (1993). Betting on Theories. Cambridge University Press.
    This book is a major contribution to decision theory, focusing on the question of when it is rational to accept scientific theories.
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  50. Michael McDermott (2008). Are Plans Necessary? Philosophical Studies 138 (2):225 - 232.
    According to classical decision theory, an agent realises at time t the option with maximum expected utility (determined by his beliefs and desires at t), where the relevant options are possible actions performed at t. I consider an alternative according to which the relevant options are in general plans, complex courses of action extending into the future.
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