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The Foundations of Causal Decision Theory
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  • Cited by 166
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    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Du, Xiaosong Leifsson, Leifur T. and Koziel, Slawomir 2017. Robust Airfoil Design Optimization Using Stochastic Expansions and Utility Theory.

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    Stefánsson, H. Orri 2017. Counterfactual Skepticism and Multidimensional Semantics. Erkenntnis,

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    Wedgwood, Ralph 2017. Must rational intentions maximize utility?. Philosophical Explorations, Vol. 20, Issue. sup2, p. 73.

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    Stefánsson, H. Orri 2017. What Is ‘Real’ in Probabilism?. Australasian Journal of Philosophy, Vol. 95, Issue. 3, p. 573.

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    Easwaran, Kenny 2017. The Tripartite Role of Belief: Evidence, Truth, and Action. Res Philosophica, Vol. 94, Issue. 2, p. 1.

    Spencer, Jack and Wells, Ian 2017. Why Take Both Boxes?. Philosophy and Phenomenological Research,

    Listwa, Daniel 2017. The Faulty Signal Problem: counterfactual asymmetries in causal decision theory and rational deliberation. Synthese,

    Huttegger, Simon M. 2017. Inductive Learning in Small and Large Worlds. Philosophy and Phenomenological Research, Vol. 95, Issue. 1, p. 90.

    Stewart, Rush T. and Quintana, Ignacio Ojea 2017. Learning and Pooling, Pooling and Learning. Erkenntnis,

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    The Foundations of Causal Decision Theory
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Book description

This book defends the view that any adequate account of rational decision making must take a decision maker's beliefs about causal relations into account. The early chapters of the book introduce the non-specialist to the rudiments of expected utility theory. The major technical advance offered by the book is a 'representation theorem' that shows that both causal decision theory and its main rival, Richard Jeffrey's logic of decision, are both instances of a more general conditional decision theory. The book solves a long-standing problem for Jeffrey's theory by showing for the first time how to obtain a unique utility and probability representation for preferences and judgements of comparative likelihood. The book also contains a major new discussion of what it means to suppose that some event occurs or that some proposition is true. The most complete and robust defence of causal decision theory available.


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