Cooperative Stochastic Differential Games [Hardcover]

Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems.

For this new edition the book has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field. The authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side.

Stochastic differential games represent one of the most complex forms of decision making under uncertainty. In particular, interactions between strategic behaviors, dynamic evolution and stochastic elements have to be considered simultaneously. The complexity of stochastic differential games generally leads to great difficulties in the derivation of solutions. Cooperative games hold out the promise of more socially optimal and group efficient solutions to problems involving strategic actions. Despite urgent calls for national and international cooperation, the absence of formal solutions has precluded rigorous analysis of this problem.

The book supplies effective tools for rigorous study of cooperative stochastic differential games. In particular, a generalized theorem for the derivation of analytically tractable payoff distribution procedurlc2