Evidential decision theory

Evidential decision theory is a school of thought within decision theory according to which the best action is the one which, conditional on your having chosen it, gives you the best expectations for the outcome. It contrasts with causal decision theory, which requires a causal connection between your actions and the desirable outcome.

Description

In a 1981 article, Allan Gibbard and William Harper characterized evidential decision theory as maximization of the expected utility $V$ of an action $A$ "calculated from conditional probabilities":^[1]

${\displaystyle V(A)=\sum \limits _{j}P(O_{j}|A)D(O_{j}),}$

where ${\displaystyle D(O_{j})}$ is the desirability of outcome $O_{j}$ and ${\displaystyle P(O_{j}|A)}$ is the conditional probability of $O_{j}$ given $A$.

Criticism

David Lewis has characterized evidential decision theory as promoting "an irrational policy of managing the news".^[2] James M. Joyce asserted, "Rational agents choose acts on the basis of their causal efficacy, not their auspiciousness; they act to bring about good results even when doing so might betoken bad news."^[3]

See also

• Causal decision theory
• Decision making
• Expected utility hypothesis
• Game theory
• Newcomb's paradox

References

1. Gibbard, A.; Harper, W.L. (1981), "Counterfactuals and two kinds of expected utility", Ifs: Conditionals, Beliefs, Decision, Chance, and Time: 153–190
2. Lewis, D. (1981), "Causal decision theory" (PDF), Australasian Journal of Philosophy, 59 (1): 5–30, doi:10.1080/00048408112340011, retrieved 2009-05-29
3. Joyce, J.M. (1999), The foundations of causal decision theory, p. 146

External links

• Causal Decision Theory at the Stanford Encyclopedia of Philosophy