I'm studying game theory and something seems weird to me.
My book says y is the probability of the row player and x is the probability of column player, both x and y are vectors.
A = [a$_i$$_j$] is the payout matrix, if a$_i$$_j$ is positive, column player pays the row player and vice versa.
So the the row player would want to minimize his payouts giving us
min y$^T$Ax with some constraint.
My question is that when I did the matrix multiplication, it dimensions do not add up.
Am I missing something??