Method
The values of payoff functions can be described by a bimatrix

			Player `B`
			`L`	`R`
Player `A`	`U`		`a_11`, `b_11`	`a_12`, `b_12`
	`D`		`a_21`, `b_21`	`a_22`, `b_22`

The values of payoff functions can be given separately for particular players
`A = [[a_11,a_12],[a_21,a_22]]`, `B = [[b_11,b_12],[b_21,b_22]]`

Matrix `A` is called a payoff matrix for player-1, matrix `B` is called a payoff matrix for player-2.

`a_(ij)` is the maximum in the column `j` of the matrix `A`, underline this value `a_(ij)`.
`b_(ij)` is the maximum in the row `i` of the matrix `B`, underline this value `b_(ij)`.
If the matrix has 1 or more cells with both values underline, then it said that the game has pure strategy nash equilibrium,
Otherwise the game has no pure strategy nash equilibrium.

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Example-1
1. Find Solution of game theory problem using Bimatrix method

Player A\Player B	L	R
U	9,9	1,10
D	10,1	2,2

Solution:

			Player `B`
			`L`	`R`
Player `A`	`U`		9, 9	1, 10
	`D`		10, 1	2, 2

			Player `B`
			`color{green}{L}`	`color{green}{R}`
Player `A`	`color{red}{U}`		9 , 9	1 , 10
	`color{red}{D}`		10 , 1	2 , 2

The cells with both entries underlined represents pure strategy nash equilibrium.
The game has pure strategy nash equilibrium : `{(D,R)}`

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