Techniques and principles of minimax theory play a key role in many areas of research, including game theory, optimization, and computational complexity. In general, a minimax problem can be formulated as min max f(x, y) (1) ", EX !lEY where f(x, y) is a function defined on the product of X and Y spaces. There are two basic issues regarding minimax problems: The first issue concerns the establishment of sufficient and necessary conditions for equality minmaxf(x, y) = maxminf(x, y). (2) "'EX !lEY !lEY "'EX The classical minimax theorem of von Neumann is a result of this type. Duality theory in linear and convex quadratic programming interprets minimax theory in a different way. The second issue concerns the establishment of sufficient and necessary conditions for values of the variables x and y that achieve the global minimax function value f(x*, y*) = minmaxf(x, y). (3) "'EX !lEY There are two developments in minimax theory that we would like to mention.

Author: Ding-Zhu Du
Binding Type: Paperback
Publisher: Springer
Published: 10/14/2011
Series: Nonconvex Optimization and Its Applications #4
Pages: 296
Weight: 0.97lbs
Size: 9.21h x 6.14w x 0.65d
ISBN: 9781461335597
Softcover Repri Edition