The epistemic state of complete ignorance is not a probability distribution. In it, we assign the same, unique ignorance degree of belief to any contingent outcome and each of its contingent, disjunctive parts. That this is the appropriate way to represent complete ignorance is established by two instruments, each individually strong enough to identify this state. They are the principle of indifference (“PI”) and the notion that ignorance is invariant under certain redescriptions of the outcome space, here developed into the “principle of invariance of ignorance” (“PII”). Both instruments are so innocuous as almost to be platitudes. Yet the literature in probabilistic epistemology has misdiagnosed them as paradoxical or defective since they...
Sometimes, ignorance is inexpressible. Lewis (2009) recognized this when he argued that we cannot kn...
Knowing that something is unknown is an important part of human cognition. While Bayesian models of ...
AbstractThis paper distinguishes between objective probability—or chance—and subjective probability....
The epistemic state of complete ignorance is not a probability distribution. In it, we assign the sa...
The epistemic state of complete ignorance is not a probability distribution. In it, we assign the sa...
This paper advocates the use of nonpurely probabilistic approaches to higher-order uncertainty. One ...
Ignorance represents a situation in which some potential outcomes are not even identified. Often the...
I argue against the Standard View of ignorance, according to which ignorance is defined as equivalen...
The principle of indifference (hereafter ‘Poi’) says that if one has no more reason to believe A tha...
Epistemic states of uncertainty play important roles in ethical and political theorizing. Theories t...
The Dunning–Kruger effect focuses our attention on the notion of invisibility of ignorance, i.e., th...
Bayesian principles of indifference imply strict commitment to states of neutrality among alternate ...
If p is an unknown probability parameter, prior ignorance of its value is appropriately expressed by...
A central problem facing a probabilistic approach to the problem of induction is the difficulty of s...
The principle of indifference states that in the absence of any relevant evidence, a rational agent ...
Sometimes, ignorance is inexpressible. Lewis (2009) recognized this when he argued that we cannot kn...
Knowing that something is unknown is an important part of human cognition. While Bayesian models of ...
AbstractThis paper distinguishes between objective probability—or chance—and subjective probability....
The epistemic state of complete ignorance is not a probability distribution. In it, we assign the sa...
The epistemic state of complete ignorance is not a probability distribution. In it, we assign the sa...
This paper advocates the use of nonpurely probabilistic approaches to higher-order uncertainty. One ...
Ignorance represents a situation in which some potential outcomes are not even identified. Often the...
I argue against the Standard View of ignorance, according to which ignorance is defined as equivalen...
The principle of indifference (hereafter ‘Poi’) says that if one has no more reason to believe A tha...
Epistemic states of uncertainty play important roles in ethical and political theorizing. Theories t...
The Dunning–Kruger effect focuses our attention on the notion of invisibility of ignorance, i.e., th...
Bayesian principles of indifference imply strict commitment to states of neutrality among alternate ...
If p is an unknown probability parameter, prior ignorance of its value is appropriately expressed by...
A central problem facing a probabilistic approach to the problem of induction is the difficulty of s...
The principle of indifference states that in the absence of any relevant evidence, a rational agent ...
Sometimes, ignorance is inexpressible. Lewis (2009) recognized this when he argued that we cannot kn...
Knowing that something is unknown is an important part of human cognition. While Bayesian models of ...
AbstractThis paper distinguishes between objective probability—or chance—and subjective probability....