Decision Systems and Nonstochastic Randomness, 2010

"Decision Systems and Non-stochastic Randomness" is the first systematic presentation and mathematical formalization (including existence theorems) of the statistical regularities of non-stochastic randomness. The results presented in this book extend the capabilities of probability theory by providing mathematical techniques that allow for the description of uncertain events that do not fit standard stochastic models. The book demonstrates how non-stochastic regularities can be incorporated into decision theory and information theory, offering an alternative to the subjective probability approach to uncertainty and the unified approach to the measurement of information. This book is intended for statisticians, mathematicians, engineers, economists or other researchers interested in non-stochastic modeling and decision theory.

Decision Systems.- Indifferent Uncertainty.- Nonstochastic Randomness.- General Decision Problems.- Experiment in Decision Problems.- Informativity of Experiment in Bayesian Decision Problems.- Reducibility of Experiments in Multistep Decision Problems.- Concluding Remarks.

Comprised of new results concerning mathematical formalization of non-stochastic mass events Can serve as a comprehensive intro to the theory of statistical regularities, introducing techniques and applications Presents a unique systems approach to decision making and decision theory with insights into the general decision and Bayesian problems Includes an appendix of classical results in the theory of functions and measured sets Includes supplementary material: sn.pub/extras