Appendix B: Solution Methods for Matrix Games

Theorem B.1    In the 2 × 2 game with matrix A, assume that there are no pure optimal strategies. If we set

images

then X* = (x*, 1 −x*), Y* = (y*, 1 − y*) are optimal mixed strategies for players I and II, respectively. The value of the game is

images

Theorem B.2    Assume that

1. An×n has an inverse A−1;

2. images

3. v(A) ≠ 0.

Set X = (x1, . . ., xn), Y = (y1, . . ., ym), and

images

If xi ≥ 0, i = 1, . . . ,n and yj ≥ 0, j = 1, . . ., n, we have that v = v(A) is the value of the game with matrix A and (X,Y) is a saddle point in mixed strategies.

Definition B.3    A game is completely mixed if every saddle point consisting of strategies X = (x1, . . ., xn) images Sn, Y = (y1, . . ., ym) images Sm satisfies the property xi > 0, i = 1, 2, . . ., n and yj > 0, j = 1, 2, . . ., m. Every row and every column is used with positive probability.

B.1   Linear Programming Methods

B.1.1   METHOD ...

Get Solutions Manual to Accompany Game Theory: An Introduction, 2nd Edition now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.