Lucia Di Giuseppe
EVIDENTIAL DECISION THEORY
Evidential Decision Theory is a branch of decision theory which advises an agent to take
actions which, conditional on it happening, maximizes the chances of the desired outcome.
As any branch of decision theory, it prescribes taking the action that maximizes utility, that
which utility equals or exceeds the utility of every other option.
The utility of each action is measured by the expected utility, the averaged by probabilities
sum of the utility of each of its possible results. How the actions can influence the
probabilities differ between the branches.
Evidential Decision Theory, on the other hand, requires no causal connection, the action
only have to be a Bayesian evidence for the desired outcome. Some critics say it
recommends auspiciousness over causal efficacy.
Evidential Decision Theory on one account can be defined as the claim that it is not
probabilities such as p(x y) that should guide one’s decision, but rather probabilities such
as p(x y│x). That is, instead of asking yourself, “what is the probability that if I were to do
X, then Y would be the case?”, a rational decision maker should ask, “what is the
probability that if I were to do X, then Y would be the case given that I do X?”
To make an example, in a Newcomb’s problem, advocates of evidential decision theory
argue that it is rationale to take one box. This is because the probability p((Take one box
1M)│take one box) is high, while p((take 2 boxes 1M)│take 2 boxes) is low.
Unfortunately, evidential decision theory is not a view without downsides. A potentially
powerful objection is that it seems to require that the decision maker can somehow ascribe
probabilities to his/her own choices.
Furthermore, according to this objection, this is incoherent because one’s own choices are
not the kind of things one can reasonably ascribe probabilities to. The reason why one has to
ascribe probabilities to one’s own choices is the simple fact that p(x│y)=
𝑃(𝑥∧𝑦)
𝑃(𝑦)
So it would be incoherent to ascribe probabilities to one’s own choices beacause, first, if
probabilities are taken to be objective it seems difficult to reconcile the idea of decision
maker making a free choice with the thought that your choices are somehow governed by
probabilistic processes. Second, similar problems arise also if probabilities are taken to be
subjective and defined in terms of preferences over best.
Evidential decision theory cannot be used as a theory of rational choice since there are cases
in which its prescriptions tell an agent to perform acts that are sure to leave her worse off
come what may.
The error in Evidential Decision Theory, it turns out, is not found in the constraints it
imposes on rational desire, but in a mistaken assumption about the epistemic standpoint
from which decision makers should evaluate their acts.
Evidential Decision Theory will thus be seen to be an essential element in our understanding
of rational desire and rational action.
Evidential Decision Theory have one peculiar feature. It turns out that the constraints it
imposes on rational preference are insufficient to fix the canons of rational belief.
The Theory in opposition is Causal Decision Theory that says only through causal process
one can influence the chances of the desired outcome.
Causal decision theory adopts principles of rational choice that attend to an act’s
consequences. It maintains that an account of rational choice must use causality to identify
the considerations that make a choice rational. Given a set of options constituting a decision
problem, decision theory recommends an option that maximizes utility, that is, an option
whose utility equals or exceeds the utility of every other option. It evaluates an option’s
utility by calculating the option’s expected utility. It uses probabilities and utilities of an
option’s possible outcomes to define an option’s expected utility. The probabilities depend
on the option. Causal decision theory takes the dependence to be causal rather than merely
evidential.
References:
https://wiki.lesswrong.com/wiki/Evidential_Decision_Theory
“An Introduction to Decision Theory” di Martin Peterson. Cambridge.
“The foundation of causal decision theory” di James M. Joyce
https://plato.stanford.edu/entries/decision-causal/ Stanford Encyclopedia of Philosophy