Evidential decision theory

In a 1981 article, Allan Gibbard and William Harper characterized evidential decision theory as maximization of the expected utility ${\displaystyle V}$ of an action ${\displaystyle A}$ "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 ${\displaystyle O_{j}}$ and ${\displaystyle P(O_{j}|A)}$ is the conditional probability of ${\displaystyle O_{j}}$ given ${\displaystyle A}$.

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]

• Ahmed, Arif (2014). Evidence, Decision and Causality. Cambridge University Press. ISBN 9781139107990.

• Causal Decision Theory at the Stanford Encyclopedia of Philosophy