Past exam of the mathematics course of the University of Cambridge / 2014 / iii / Paper 37 / 4

Use net monetary gain as payoff and order each player's pure strategies as $1,2,4$. The payoff matrix for the first player isThe second player's matrix is $-A$. Equal choices return both stakes, so the diagonal is zero; when the first player wins, their net gain is the other's stake, and when they lose it is minus their own stake. This is a matrix game, hence a zero-sum game and a normal-form game.

The game is degenerate in the nondegeneracy of a bimatrix game sense. Against the first player's pure strategy $4$, the second player's choices $1$ and $2$ are both best responses, with payoff four. A mixed strategy of support size one therefore has two pure best responses. The usual Lemke-Howson algorithm path needs additional tie handling or perturbation in such a game; the zero-sum game structure gives a simpler direct linear program.

Add five to every entry of the first player's matrix, obtainingThis does not change either player's best responses or Nash equilibria; it raises the game value by five. Since all entries are positive, its value $v_B$ is positive. If $p$ is a row mixed strategy guaranteeing $v_B$, put $x=p/v_B$. Then $B^{T}x\ge 1$ and $1^{T}x=1/v_B$.

Conversely any feasible $x$ has $s=1^{T}x>0$, and $p=x/s$ guarantees payoff $1/s$ in the shifted game. Maximizing that guaranteed payoff is therefore equivalent to minimizing $s$ under $B^{T}x\ge 1$, $x\ge 0$. These are precisely the displayed constraints. The dual program maximizes $1^{T}y$ subject to $By\le 1$, $y\ge 0$; normalizing an optimal $y$ gives the column strategy. This is positive-payoff linear programming for a matrix game.

Introduce nonnegative surplus variablesAt the proposed starting basic feasible solution, the basic variables are $x_1,r_1,r_2$ and the nonbasic variables are $x_2,x_3,r_3$. Its simplex dictionary, with objective $z=x_1+x_2+x_3$, isIncrease $x_3$ to decrease $z$. The simplex ratio test gives limits $1/5$ from $x_1$, $1/21$ from $r_1$, and $3/31$ from $r_2$. The smallest is $1/21$, so $x_3$ enters and $r_1$ leaves. After this single pivot the dictionary isAll objective coefficients of nonbasic variables are strictly positive. Thus the simplex method has reached its unique optimum:The feasible dual vector $y=(1/21,0,4/21)$ has the same objective, providing an independent weak duality certificate. Normalization givesThese are all the equilibria: the dual's strict slack in row two forces $p_2=0$, and the primal's strict slack in column two forces $q_2=0$. Equality of the two active row and column payoffs then fixes the displayed probabilities. The value is the first player's expected net loss; the second gains $4/5$.

For a fixed number choice, increasing one's own stake changes only the amount lost when one loses. It does not change the amount won, which is the opponent's stake, or the zero payoff of a tie. Thus doubling is either weakly dominated by retaining the original stake or payoff-equivalent to it. This establishes that there is no strategic advantage in doubling, but does not imply strict harm in every equilibrium.

For the first player, each of the two equilibrium choices loses with positive probability: choice one loses against the second player's four, and choice four loses against their one. Doubling either therefore gives a strictly smaller expected payoff than $-4/5$. By contrast, against the first player's support $\{1,4\}$, the second player's choices one and four either win or tie. Their own stake is never lost, so doubling it does not change their payoff.

More precisely, retain the first player's original-stake probabilities $(4/5,0,1/5)$. The second player may split their total probability $1/5$ on choice one, and $4/5$ on choice four, arbitrarily between original and double stakes. The first player's unused choice two has payoff at most $(1/5)2-(4/5)2=-6/5<-4/5$, even when the second player doubles their one stake. The doubled first-player choices are also worse. The second player's choice two, with either stake, is worse against the displayed first-player strategy. Hence these splits remain Nash equilibria of the enlarged zero-sum game.

The first player should not double; the second player is indifferent between doubling and retaining the original stakes on their equilibrium choices. This distinction is an example of weak domination does not exclude equilibrium strategies.