m n
  matrix A
  matrix B
  

eg. the file game is for a game with m=3 n=2:

  3 2
  0 6
  2 5
  3 3
  
  1 0
  0 2
  4 3
  

  % setupnash game game1 game2
  

produces two H-representations, game1 and game2, one for each player. To get the equilibria, run

  %  nash game1  game2
  

or

  %  2nash game1  game2
  

Each row beginning 1 is a strategy for the row player yielding a NE with each row beginning 2 listed immediately above it.The payoff for player 2 is the last number on the line beginning 1, and vice versa. Eg: first two lines of output: player 1 uses row probabilities 2/3 2/3 0 resulting in a payoff of 2/3 to player 2.Player 2 uses column probabilities 1/3 2/3 yielding a payoff of 4 to player 1. If both matrices are nonnegative and have no zero columns, you may instead use setupnash2:

  % setupnash2 game game1 game2

Now the polyhedra produced are polytopes. The output  of nash in this case is a list of unscaled probability vectors x and y. To normalize, divide each vector by v = 1^T x and u=1^T y.u and v are the payoffs to players 1 and 2 respectively. In this case, lower bounds on the payoff functions to either or both players may be included. To give a lower bound of r on the payoff for player 1 add the options to file game2  (yes that is correct!)To give a lower bound of r on the payoff for player 2 add the options to file game1

  minimize
  0 1 1 ... 1    (n entries to begiven)
  bound   1/r;    ( note: reciprocal of r)

If you do not wish to use the 2-cpu program 2nash, please read the following. If m is greater than n then nash usually runs faster by transposing the players. This is achieved by running:

 %  nash game2  game1

If you wish to construct the game1 and game2 files by hand, see the m[blue]lrslib user manualm[][1]