Bayesian Decision Theory and Stochastic Independence

Bayesian Decision Theory and Stochastic Independence

Stochastic independence has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory. Bayesian decision theorists such as Savage can be criticized for being silent about stochastic independence. From their current preference axioms, they can derive no more than t...

Independence and Qualitative Decision Theory

Probabilistic independence has proved to be a fundamental tool that can dramatically simplify the task of eliciting, representing, and computing with probabilities. We advance the position that notions of utility independence can serve similar functions when reasoning about preferences and utilities during decision making. In this paper we first summarize existing results and definitions concer...

Bayesian Decision Theory and Psychophysics

We argue that Bayesian decision theory provides a good theoretical framework for visual perception. Such a theory involves a likelihood function specifying how the scene generates the image(s), a prior assumption about the scene, and a decision rule to determine the scene interpretation. This is illustrated by describing Bayesian theories for individual visual cues and showing that perceptual b...

Bayesian Decision Making Theory

Utility Independence in a Qualitative Decision Theory

Qualitative accounts of utility modeling and decision theory o er the prospect of rea soning about preference and decision making without requiring hard to obtain numerical probabilities and utilities It is plausible that such accounts can be found because qualita tive criteria in particular dominance seems to play a large role in human decision making the formal quantitative apparatus of maxi ...