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2 311 kr
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This book is devoted to a unified treatment of Competitive Markov Decision Processes. It examines these processes from the standpoints of modeling and of optimization, providing newcomers to the field with an accessible account of algorithms, theory, and applications, while also supplying specialists with a comprehensive survey of recent developments. The treatment is self-contained, requiring only some knowledge of linear algebra and real analysis. Topics covered include: Mathematical programming: Markov decision processes (the non-competitive case), and stochastic games via mathematical programming.- Existence, structure and applications: Summable stochastic games, average-reward stochastic games and applications and special classes of stochastic games.- Appendices on: matrix games, bimatrix games and nonlinear programming; a theorem of Hardy and Littlewood; Markov chains; and complex varieties and the limit discount equation.
2 311 kr
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Since Markov decision processes can be viewed as a special noncompeti tive case of stochastic games, we introduce the new terminology Competi tive Markov Decision Processes that emphasizes the importance of the link between these two topics and of the properties of the underlying Markov processes.