Cargando…

Decision Systems and Nonstochastic Randomness

"Decision Systems and Nonstochastic Randomness" presents the first mathematical formalization of the statistical regularities of non-stochastic randomness and demonstrates how these regularities extend the standard probability-based model of decision making under uncertainty, allowing for...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Ivanenko, V. I. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Temas:
Acceso en línea:Texto Completo

MARC

LEADER 00000nam a22000005i 4500
001 978-1-4419-5548-7
003 DE-He213
005 20220116164841.0
007 cr nn 008mamaa
008 100528s2010 xxu| s |||| 0|eng d
020 |a 9781441955487  |9 978-1-4419-5548-7 
024 7 |a 10.1007/978-1-4419-5548-7  |2 doi 
050 4 |a QA273.A1-274.9 
072 7 |a PBT  |2 bicssc 
072 7 |a PBWL  |2 bicssc 
072 7 |a MAT029000  |2 bisacsh 
072 7 |a PBT  |2 thema 
072 7 |a PBWL  |2 thema 
082 0 4 |a 519.2  |2 23 
100 1 |a Ivanenko, V. I.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Decision Systems and Nonstochastic Randomness  |h [electronic resource] /  |c by V. I. Ivanenko. 
250 |a 1st ed. 2010. 
264 1 |a New York, NY :  |b Springer New York :  |b Imprint: Springer,  |c 2010. 
300 |a XII, 272 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a 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. 
520 |a "Decision Systems and Nonstochastic Randomness" presents the first mathematical formalization of the statistical regularities of non-stochastic randomness and demonstrates how these regularities extend the standard probability-based model of decision making under uncertainty, allowing for the description of uncertain mass events that do not fit standard stochastic models. Each self-contained chapter of this neatly-structured monograph includes a detailed introduction and summary of its contents. The included results are presented not only with rigorous proofs but also through numerous intuitive examples. An appendix is provided which includes classic results from the theory of functions and measured sets as well as decision theory, offering an overview of the necessary prerequisites. The formalism of statistical regularities developed in this book will have a significant influence on decision theory and information theory as well as numerous other disciplines. Because of these far-reaching implications, this book may be a useful resource for statisticians, mathematicians, engineers, economists and other utilizing nonstochastic modeling and decision theory. 
650 0 |a Probabilities. 
650 0 |a Mathematics. 
650 0 |a Business mathematics. 
650 0 |a Statistics . 
650 0 |a Game theory. 
650 0 |a Operations research. 
650 1 4 |a Probability Theory. 
650 2 4 |a Applications of Mathematics. 
650 2 4 |a Business Mathematics. 
650 2 4 |a Statistical Theory and Methods. 
650 2 4 |a Game Theory. 
650 2 4 |a Operations Research and Decision Theory. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9781441955470 
776 0 8 |i Printed edition:  |z 9781441955586 
776 0 8 |i Printed edition:  |z 9781489984968 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-1-4419-5548-7  |z Texto Completo 
912 |a ZDB-2-SMA 
912 |a ZDB-2-SXMS 
950 |a Mathematics and Statistics (SpringerNature-11649) 
950 |a Mathematics and Statistics (R0) (SpringerNature-43713)