This paper aims to make explicit the methodological conditions that should be satisfied for the Bayesian model to be used as a normative model of human probability judgment. After noticing the lack of a clear definition of Bayesianism in the psychological literature and the lack of justification for using it, a classic definition of subjective Bayesianism is recalled, based on the following three criteria: An epistemic criterion, a static coherence criterion and a dynamic coherence criterion. Then it is shown that the adoption of this framework has two kinds of implications. The first one regards the methodology of the experimental study of probability judgment. The Bayesian framework creates pragmatic constraints on the methodology that ar...
Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue t...
We confess that the first part of our title is somewhat of a misnomer. Bayesian reasoning is a norma...
In this thesis we present a review of the Bayesian approach to Statistical Inference. In Chapter One...
Abstract This paper aims to make explicit the methodological conditions that should be satisfied for...
A Bayesian mind is, at its core, a rational mind. Bayesianism is thus well-suited to predict and exp...
Recent debates in the psychological literature have raised questions about what assumptions underpin...
Recent debates in the psychological literature have raised questions about the assumptions that unde...
honors thesisCollege of HumanitiesPhilosophyJonah N. SchuphachIn this paper I push for and defend th...
Bayesianism is the position that scientific reasoning is probabilistic and that probabilities are ad...
AbstractIn the current discussion about the capacity of Bayesianism in reasoning under uncertainty, ...
The thesis is an exposition and defence of Bayesianism as the preferred methodology of reasoning und...
Abstract: The prominence of Bayesian modeling of cognition has increased recently largely because of...
Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have ...
Judgements in the real-world often inherently involve uncertainty, from the mundane: "do those cloud...
Some misconceptions about subjective probability and Bayesian inference exist, that can be obstacles...
Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue t...
We confess that the first part of our title is somewhat of a misnomer. Bayesian reasoning is a norma...
In this thesis we present a review of the Bayesian approach to Statistical Inference. In Chapter One...
Abstract This paper aims to make explicit the methodological conditions that should be satisfied for...
A Bayesian mind is, at its core, a rational mind. Bayesianism is thus well-suited to predict and exp...
Recent debates in the psychological literature have raised questions about what assumptions underpin...
Recent debates in the psychological literature have raised questions about the assumptions that unde...
honors thesisCollege of HumanitiesPhilosophyJonah N. SchuphachIn this paper I push for and defend th...
Bayesianism is the position that scientific reasoning is probabilistic and that probabilities are ad...
AbstractIn the current discussion about the capacity of Bayesianism in reasoning under uncertainty, ...
The thesis is an exposition and defence of Bayesianism as the preferred methodology of reasoning und...
Abstract: The prominence of Bayesian modeling of cognition has increased recently largely because of...
Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have ...
Judgements in the real-world often inherently involve uncertainty, from the mundane: "do those cloud...
Some misconceptions about subjective probability and Bayesian inference exist, that can be obstacles...
Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue t...
We confess that the first part of our title is somewhat of a misnomer. Bayesian reasoning is a norma...
In this thesis we present a review of the Bayesian approach to Statistical Inference. In Chapter One...