Sprache: Englisch
Verlag: Dover Publications, Incorporated, 2014
ISBN 10: 0486780643 ISBN 13: 9780486780641
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Verlag: Springer, 1996
ISBN 10: 0387946284 ISBN 13: 9780387946283
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Hardcover. Zustand: ex library-good. Applications of Mathematics. Stochastic Modelling and Applied Probability 32. xi, 244 p. 24 cm. Ex library with labels on spine and inside rear cover, ink stamps on top edge and title.
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1996. 256 p. Unread book. Very good condition. Minimum traces of storage. 9780387946283 Sprache: Englisch Gewicht in Gramm: 522 Hardcover: 15.6 x 1.7 x 23.4 cm.
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 260 | Sprache: Englisch | Produktart: Bücher | The theory of probability began in the seventeenth century with attempts to calculate the odds of winning in certain games of chance. However, it was not until the middle of the twentieth century that mathematicians de veloped general techniques for maximizing the chances of beating a casino or winning against an intelligent opponent. These methods of finding op timal strategies for a player are at the heart of the modern theories of stochastic control and stochastic games. There are numerous applications to engineering and the social sciences, but the liveliest intuition still comes from gambling. The now classic work How to Gamble If You Must: Inequalities for Stochastic Processes by Dubins and Savage (1965) uses gambling termi nology and examples to develop an elegant, deep, and quite general theory of discrete-time stochastic control. A gambler "controls" the stochastic pro cess of his or her successive fortunes by choosing which games to play and what bets to make.
Sprache: Englisch
Verlag: Springer New York, Springer New York, 2011
ISBN 10: 1461284678 ISBN 13: 9781461284673
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The theory of probability began in the seventeenth century with attempts to calculate the odds of winning in certain games of chance. However, it was not until the middle of the twentieth century that mathematicians de veloped general techniques for maximizing the chances of beating a casino or winning against an intelligent opponent. These methods of finding op timal strategies for a player are at the heart of the modern theories of stochastic control and stochastic games. There are numerous applications to engineering and the social sciences, but the liveliest intuition still comes from gambling. The now classic work How to Gamble If You Must: Inequalities for Stochastic Processes by Dubins and Savage (1965) uses gambling termi nology and examples to develop an elegant, deep, and quite general theory of discrete-time stochastic control. A gambler 'controls' the stochastic pro cess of his or her successive fortunes by choosing which games to play and what bets to make.