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  1. J. McKenzie Alexander (2012). Decision Theory Meets the Witch of Agnesi. Journal of Philosophy 109 (12):712-727.
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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. Marcus Arvan (2015). How to Rationally Approach Life's Transformative Experiences. Philosophical Psychology 28 (8):1199-1218.
    In a widely discussed forthcoming article, “What you can't expect when you're expecting,” L. A. Paul challenges culturally and philosophically traditional views about how to rationally make major life-decisions, most specifically the decision of whether to have children. The present paper argues that because major life-decisions are transformative, the only rational way to approach them is to become resilient people: people who do not “over-plan” their lives or expect their lives to play out “according to plan”—people who understand that beyond (...)
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  4. Robert Audi (1986). Action Theory as a Resource for Decision Theory. Theory and Decision 20 (3):207-221.
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  5. S. K. Berninghaus, S. J. Brams, P. H. Edelman, J. Esteban, I. Fischer, P. C. Fishburn, G. Gigliotti, W. Güth, R. D. Luce & P. Modesti (2003). Theory and Decision. Theory and Decision 55 (392).
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  6. Magnus Boman (1999). Norms in Artificial Decision Making. Artificial Intelligence and Law 7 (1):17-35.
    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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  7. Michael Clark & Nicholas Shackel (2003). Decision Theory, Symmetry and Causal Structure: Reply to Meacham and Weisberg. Mind 112 (448):691-701.
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  8. 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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  9. 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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  10. Daniel Dohrn (2015). Egan and Agents: How Evidential Decision Theory Can Deal with Egan’s Dilemma. Synthese 192 (6):1883-1908.
    Andy Egan has presented a dilemma for decision theory. As is well known, Newcomb cases appear to undermine the case for evidential decision theory . However, Egan has come up with a new scenario which poses difficulties for causal decision theory. I offer a simple solution to this dilemma in terms of a modified EDT. I propose an epistemological test: take some feature which is relevant to your evaluation of the scenarios under consideration, evidentially correlated with the actions under consideration (...)
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  11. P. Dowe (1998). A Problem for Causal Decision Theory: Causality and Identity. Communication and Cognition. Monographies 31 (4):325-338.
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  12. Ellery Eells (2000). The Foundations of Causal Decision Theory [Review]. [REVIEW] British Journal for the Philosophy of Science 51 (4):893-900.
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  13. R. Allen Gardner & John B. Forsythe (1961). Supplementary Report: Two-Choice Decision Behavior with Many Alternative Events. Journal of Experimental Psychology 62 (6):631.
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  14. Hilary Greaves (2013). Epistemic Decision Theory. Mind 122 (488):915-952.
    I explore the prospects for modelling epistemic rationality (in the probabilist setting) via an epistemic decision theory, in a consequentialist spirit. Previous work has focused on cases in which the truth-values of the propositions in which the agent is selecting credences do not depend, either causally or merely evidentially, on the agent’s choice of credences. Relaxing that restriction leads to a proliferation of puzzle cases and theories to deal with them, including epistemic analogues of evidential and causal decision theory, and (...)
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  15. York Hagmayer & Björn Meder (2008). Causal Learning Through Repeated Decision Making. In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society 179--184.
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  16. 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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  17. C. A. Hooker, J. J. Leach & E. F. Mcclennen (1980). Foundations and Applications of Decision Theory. Philosophy and Phenomenological Research 41 (1):252-254.
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  18. James Joyce (2002). Levi on Causal Decision Theory and the Possibility of Predicting One's Own Actions. Philosophical Studies 110 (295):69-102.
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  19. James Joyce (1995). Decision Theory. Philosophical Books 36 (4):225-237.
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  20. James M. Joyce (2007). Are Newcomb Problems Really Decisions? Synthese 156 (3):537 - 562.
    Richard Jeffrey long held that decision theory should be formulated without recourse to explicitly causal notions. Newcomb problems stand out as putative counterexamples to this ‘evidential’ decision theory. Jeffrey initially sought to defuse Newcomb problems via recourse to the doctrine of ratificationism, but later came to see this as problematic. We will see that Jeffrey’s worries about ratificationism were not compelling, but that valid ratificationist arguments implicitly presuppose causal decision theory. In later work, Jeffrey argued that Newcomb problems are not (...)
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  21. James Michael Joyce (1992). The Axiomatic Foundations of Bayesian Decision Theory. Dissertation, University of Michigan
    Bayesian decision theorists argue that rational agents should always perform acts that maximize subjective expected utility. To justify this claim, they prove representation theorems which are designed to show that any decision maker whose beliefs and desires satisfy reasonable axiomatic constraints will necessarily behave like an expected utility maximizer. The existence of such a representation result is a prerequisite for any adequate account of rational choice because one is only able to determine what a decision theory says about beliefs and (...)
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  22. Joseph B. Kadane, Teddy Seidenfeld & Mark J. Schervish, A Rubinesque Theory of Decision.
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  23. Mortimer Raymond Kadish (1950). Toward a Theory of Decision. Dissertation, Columbia University
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  24. Christian List & Franz Dietrich, Reason-Based Choice and Context-Dependence: An Explanatory Framework.
    We introduce a “reason-based” framework for explaining and predicting individual choices. It captures the idea that a decision-maker focuses on some but not all properties of the options and chooses an option whose motivationally salient properties he/she most prefers. Reason-based explanations allow us to distinguish between two kinds of context-dependent choice: the motivationally salient properties may (i) vary across choice contexts, and (ii) include not only “intrinsic” properties of the options, but also “context-related” properties. Our framework can accommodate boundedly rational (...)
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  25. Gary Malinas (1993). Reflective Coherence and Newcomb Problems: A Simple Solution. Theory and Decision 35 (2):151-166.
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  26. Laurence T. Maloney (2002). Statistical Decision Theory and Biological Vision. In Dieter Heyer & Rainer Mausfeld (eds.), Perception and the Physical World. Wiley 145--189.
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  27. Kenneth L. Manders (1979). The Theory of All Substructures of a Structure: Characterisation and Decision Problems. Journal of Symbolic Logic 44 (4):583-598.
    An infinitary characterisation of the first-order sentences true in all substructures of a structure M is used to obtain partial reduction of the decision problem for such sentences to that for Th(M). For the relational structure $\langle\mathbf{R}, \leq, +\rangle$ this gives a decision procedure for the ∃ x∀ y-part of the theory of all substructures, yet we show that the ∃ x 1x 2 ∀ y-part, and the entire theory, is Π 1 1 -complete. The theory of all ordered subsemigroups (...)
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  28. 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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  29. Herman Mcdaniel (1970). Applications of Decision Tables a Reader.
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  30. Björn Meder & York Hagmayer (2009). Causal Induction Enables Adaptive Decision Making. In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
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  31. A. Morton (1999). Mark Kaplan, Decision Theory as Philosophy. British Journal for the Philosophy of Science 50:505-507.
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  32. Sahlin Nils-Eric, Vareman Niklas, Galavotti Maria Carla & Scazzieri Roberto (2008). Three Types of Decision Theory. In Maria-Carla Galavotti (ed.), Reasoning, Rationality and Probability. Csli Publications
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  33. 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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  34. J. M. P. (1966). The Logic of Decision. [REVIEW] Review of Metaphysics 19 (4):813-814.
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  35. S. Pandey (1980). The Logic of Decision. Indian Philosophical Quarterly 8 (1):77.
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  36. Philip Pettit (1989). Decision Theory, Political Theory and the Hats Hypothesis. In Fred D'Agostino & I. C. Jarvie (eds.), Freedom and Rationality. Reidel 23--34.
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  37. Solomon L. Pollack, Harry T. Hicks & William J. Harrison (1971). Decision Tables Theory and Practice.
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  38. John L. Pollock, Locally Global Planning.
    It is conjectured that MDP and POMDP planning will remain unfeasible for complex domains, so some form of ÒclassicalÓ decision-theoretic planning is sought. However, local plans cannot be properly compared in terms of their expected values, because those values will be affected by the other plans the agent has adopted. Plans must instead be merged into a single Òmaster-planÓ, and new plans evaluated in terms of their contribution to the value of the master plan. To make both the construction and (...)
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  39. Wlodek Rabinowicz (2000). Value and Choice Some Common Themes in Decision Theory and Moral Philosophy. Lund Universitetstrycheriet.
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  40. Gerard Radnitzky (1984). Sicence, Tecnology, and Political Decision. From the Creation of a Theory to the Consequences of its Application. Revista Portuguesa de Filosofia 40 (3):307-317.
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  41. John Piers Rawling (1989). Choice and Action: In Defense of Richard Jeffrey's "Logic of Decision". Dissertation, University of California, Berkeley
    Richard Jeffrey's Logic of Decision has come under fire on the grounds that it appears to prescribe irrational decisions under certain circumstances . A number of authors see the source of Jeffrey's difficulty as a lack of sensitivity to causal distinctions of a certain kind. They have proposed modifications of Jeffrey's theory to overcome this putative deficiency. David Lewis argues, convincingly, that these modified theories are all more or less the same. In essence, they all augment the Logic of Decision (...)
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  42. Susanna Rinard (2015). A Decision Theory for Imprecise Probabilities. Philosophers' Imprint 15 (7).
    Those who model doxastic states with a set of probability functions, rather than a single function, face a pressing challenge: can they provide a plausible decision theory compatible with their view? Adam Elga and others claim that they cannot, and that the set of functions model should be rejected for this reason. This paper aims to answer this challenge. The key insight is that the set of functions model can be seen as an instance of the supervaluationist approach to vagueness (...)
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  43. Nils-Eric Sahlin & Niklas Vareman (2008). Three Types of Decision Theory. In Maria-Carla Galavotti (ed.), Reasoning, Rationality and Probability. Csli Publications 37--59.
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  44. Wolfgang Schwarz (forthcoming). Lost Memories and Useless Coins: Revisiting the Absentminded Driver. Synthese:1-26.
    The puzzle of the absentminded driver combines an unstable decision problem with a version of the Sleeping Beauty problem. Its analysis depends on the choice between “halfing” and “thirding” as well as that between “evidential” and “causal” decision theory. I show that all four combinations lead to interestingly different solutions, and draw some general lessons about the formulation of causal decision theory, the interpretation of mixed strategies and the connection between rational credence and objective chance.
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  45. John Shoemaker (unknown). A Critical Look At Mark Kaplan's "Decision Theory As Philosophy". Proceedings of the Heraclitean Society 21.
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  46. J. H. Sobel (1999). Kaplan, M.-Decision Theory as Philosophy. Philosophical Books 40:62-64.
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  47. Patrick Suppes (1967). Decision Theory. In Paul Edwards (ed.), The Encyclopedia of Philosophy. New York, Macmillan 2--310.
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  48. Patrick Suppes (1961). The Philosophical Relevance of Decision Theory. Journal of Philosophy 58 (21):605-614.
  49. Mc-T. Tai (2003). Who Makes the Decision? Synthesis Philosophica 18 (1/2):355-364.
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  50. Nassim N. Taleb & Avital Pilpel (2007). Epistemology and Risk Management. Risk and Regulation 13:6--7.
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