The Bayes Blind Spot of a Bayesian Agent is the set of probability measures on a Boolean algebra that are absolutely continuous with respect to the background probability measure (prior) of a Bayesian Agent on the algebra and which the Bayesian Agent cannot learn by conditionalizing no matter what (possibly uncertain) evidence he has about the elements in the Boolean algebra. It is shown that if the Boolean algebra is finite, then the Bayes Blind Spot is a very large set: it has the same cardinality as the set of all probability measures (continuum); it has the same measure as the measure of the set of all probability measures (in the natural measure on the set of measures); and is a ``fat'' (second Baire category) set in topological sense ...
With the advent of high-performance computing, Bayesian methods are becoming increasingly popular to...
With the advent of high-performance computing, Bayesian methods are becoming increasingly popular to...
We consider an infinite collection of agents who make decisions, sequentially, about an unknown unde...
The Bayes Blind Spot of a Bayesian Agent is the set of probability measures on a Boolean algebra tha...
The Bayes Blind Spot of a Bayesian Agent is, by definition, the set of probability measures on a Boo...
We investigate the general properties of general Bayesian learning, where “general Bayesian learning...
Bayes logics based on Bayes conditionalization as a probability updating mechanism have recently bee...
AbstractIn the current discussion about the capacity of Bayesianism in reasoning under uncertainty, ...
We investigate the general properties of general Bayesian learning, where ``general Bayesian learnin...
In the paper [http://philsci-archive.pitt.edu/14136] a hierarchy of modal logics have been defined t...
In Bayesian belief revision a Bayesian agent revises his prior belief by conditionalizing the prior ...
We continue the investigations initiated in the recent papers \cite{BGyR,GyBLst} where Bayes logics ...
In this work, we discuss Bayesian estimation of multinomial probabilities associated with a finite ...
This paper considers the simple problem of abduction in the framework of Bayes theorem, i.e. computi...
With the advent of high-performance computing, Bayesian methods are becoming increasingly popular to...
With the advent of high-performance computing, Bayesian methods are becoming increasingly popular to...
We consider an infinite collection of agents who make decisions, sequentially, about an unknown unde...
The Bayes Blind Spot of a Bayesian Agent is the set of probability measures on a Boolean algebra tha...
The Bayes Blind Spot of a Bayesian Agent is, by definition, the set of probability measures on a Boo...
We investigate the general properties of general Bayesian learning, where “general Bayesian learning...
Bayes logics based on Bayes conditionalization as a probability updating mechanism have recently bee...
AbstractIn the current discussion about the capacity of Bayesianism in reasoning under uncertainty, ...
We investigate the general properties of general Bayesian learning, where ``general Bayesian learnin...
In the paper [http://philsci-archive.pitt.edu/14136] a hierarchy of modal logics have been defined t...
In Bayesian belief revision a Bayesian agent revises his prior belief by conditionalizing the prior ...
We continue the investigations initiated in the recent papers \cite{BGyR,GyBLst} where Bayes logics ...
In this work, we discuss Bayesian estimation of multinomial probabilities associated with a finite ...
This paper considers the simple problem of abduction in the framework of Bayes theorem, i.e. computi...
With the advent of high-performance computing, Bayesian methods are becoming increasingly popular to...
With the advent of high-performance computing, Bayesian methods are becoming increasingly popular to...
We consider an infinite collection of agents who make decisions, sequentially, about an unknown unde...