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  1. Push the Button.Arif Ahmed - 2012 - Philosophy of Science 79 (3):386-395.
    Opponents of Causal Decision Theory (CDT) sometimes claim (i) that it gives the wrong advice in Egan-style cases, where the CDT-endorsed act brings news that it causes a bad outcome; (ii) that CDT gives the right advice in Newcomb cases, where it is known in advance that the CDT-act causes you to be richer than the alternative. This paper argues that (i) and (ii) cannot both be true if rational preference over acts is transitive.
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  • Probability Theory. The Logic of Science.Edwin T. Jaynes - 2002 - Cambridge University Press: Cambridge. Edited by G. Larry Bretthorst.
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  • Bayesian Measures of Confirmation from Scoring Rules.Steven J. van Enk - 2014 - Philosophy of Science 81 (1):101-113.
    I show how scoring rules, interpreted as measuring the inaccuracy of a set of degrees of belief, may be exploited to construct confirmation measures as used in Bayesian confirmation theory. I construct two confirmation measures from two particular standard scoring rules. One of these measures is genuinely new, the second is trivially ordinally equivalent to the difference measure. These two measures are tested against three well-known measures of confirmation in a simple but illuminating case that contains in a natural way (...)
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  • Causal decision theory.David Lewis - 1981 - 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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  • The Logic of Decision.Richard C. Jeffrey - 1965 - New York, NY, USA: University of Chicago Press.
    "[This book] proposes new foundations for the Bayesian principle of rational action, and goes on to develop a new logic of desirability and probabtility."—Frederic Schick, _Journal of Philosophy_.
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  • Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.
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  • The Foundations of Statistics.Leonard J. Savage - 1956 - Philosophy of Science 23 (2):166-166.
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