The Culture — a human/machine symbiotic society — has thrown up many great Game Players, and one of the greatest is Gurgeh Jernau Morat Gurgeh. The Player of Games. Master of every board, computer and strategy. Bored with success, Gurgeh travels to the Empire of Azad, cruel and incredibly wealthy, to try their fabulous game. . . a game so complex, so like life itself, that the winner becomes emperor. Mocked, blackmailed, almost murdered, Gurgeh accepts the game, and with it the challenge of his life — and very possibly his death. The Culture Series Consider Phlebas The Player of Games Use of Weapons The State of the Art Excession Inversions Look to Windward Matter Surface Detail The Hydrogen Sonata

Buy now to get the main key ideas from Iain M. Banks's The Player of Games Jernau Morat Gurgeh is a professional game player in a utopian, post-scarcity space society called the Culture. Having mastered every tactic and strategy, Gurgeh has become bored with easy victories. In The Player of Games (1988), novelist Iain M. Banks takes us on a voyage with Gurgeh as he travels to a distant, barbaric empire to participate in a game so complex that the winner becomes emperor. As he is blackmailed and almost killed, Gurgeh discovers that he is a pawn in a much bigger game played by the Culture.

The Culture -- a human/machine symbiotic society -- has thrown up many great Game Players, and one of the greatest is Gurgeh. Jernau Morat Gurgeh. The Player of Games. Master of every board, computer and strategy. Bored with success, Gurgeh travels to the Empire of Azad, cruel and incredibly wealthy, to try their fabulous game. . .a game so complex, so like life itself, that the winner becomes emperor. Mocked, blackmailed, almost murdered, Gurgeh accepts the game, and with it the challenge of his life -- and very possibly his death.

Science fiction-novel.

Summary A Bayesian Theory of Games introduces a new game theoretic equilibrium concept: Bayesian equilibrium by iterative conjectures (BEIC). The new equilibrium concept achieves consistencies in results among different types of games that current games theory at times fails to. BEIC requires players to make predictions on the strategies of other players starting from first order uninformative predictive distribution functions (or conjectures) and keep updating with Bayesian statistical decision theoretic and game theoretic reasoning until a convergence of conjectures is achieved. In a BEIC, conjectures are consistent with the equilibrium or equilibriums they supported and so rationality is achieved for actions, strategies and beliefs and (statistical) decision rule. Given its ability to typically select only a unique equilibrium in games, the BEIC approach is capable of analyzing a larger set of games than current games theory, including games with noisy inaccurate observations and games with multiple sided incomplete information games. Key Features Provides a unified and consistent analysis of many categories of games. Its solution algorithm is iterative and has good computation properties. Can analyze more types of games than current existing games theory. The equilibrium concept and solution algorithm are based on Bayesian statistical decision theory. In the new equilibrium, rationality is achieved for action, strategy, belief (both prior and posterior) and decision rule. Beliefs are the results of optimization exercises of players. Uses first order uninformative conjectures and reaction functions to derive higher and higher orders of conjectures until a convergence of conjectures is achieved. Has great application value for it could solve many types of games and could model beliefs. The Author Dr Jimmy Teng currently teaches at the School of Economics of the University of Nottingham (Malaysia Campus). He is the author of many articles and two books. He received his economics PhD from the University of Toronto. He also earned a PhD in political Science and a MS in statistics from Duke University. He previously held research and teaching positions in Academia Sinica, National Taiwan University and Nanyang Technological University Readership Games theorists, decision theorists, economists, mathematicians, statisticians, operational researchers, social scientists, management researchers, public policy researchers, computer scientists Contents Preface Acknowledgments About the author Introduction Sequential games with incomplete information and noisy inaccurate observation; introduction; an inflationary game; Bayesian iterative conjectures algorithm as a Bayes decision rule; conclusions Sequential games with perfect and imperfect information; introduction; the Bayesian iterative conjecture algorithm, sub-game perfect equilibrium and perfect Bayesian equilibrium; solving sequential games of incomplete and perfect information; multiple-sided incomplete information sequential games with perfect information; conclusions Simultaneous games; introduction; complete information simultaneous games; BEIC and refinements of Nash equilibrium; simultaneous games with incomplete information; conclusions Conclusions References Index