Measure Transportation and Statistical Decision Theory

Decision Theory = Performance Measure Theory + Uncertainty Theory

The decision theory is defined typically as the combination of utility theory and probability theory. In this paper we generalize the decision theory as the performance measure theory and uncertainty theory. Intelligent agents look for approximate optimal decisions under bounded resources and uncertainty. The $-calculus process algebra for problem solving applies the cost performance measures t...

Statistical decision theory and evolution.

Two recent articles by Geisler and Diehl use Bayesian statistical decision theory to model the co-evolution of predator and prey in a simple, game-like environment. The prey is characterized by its coloration. The predator is characterized by the chromatic sensitivity of its visual system and its willingness to attack. The authors demonstrate how the coloration of prey and the perceptual system...

Statistical Decision and Learning Theory

This paper reviews and contrasts the basic elements of statistical decision theory [1–4] and statistical learning theory [5–7]. It is not intended to be a comprehensive treatment of either subject, but rather just enough to draw comparisons between the two. Throughout this paper, let X denote the input to a decision-making process and Y denote the correct response or output (e.g., the value of ...

Statistical Decision Fusion Theory

By combining information theory, statistical decision theory, and maximum entropy to address the decision fusion problems, a statistical decision fusion theory is obtained. The theory explains why decision fusion is so difficult and why the performance of decision fusion systems does not always meet expectations. The theory suggests how statistical decision systems such as the conceptual "Famil...

Statistical Decision Theory: Concepts, Methods and Applications