G1 := RandDisGame(4, 4):
G2 := RandDisGame(5, 7):
print(Matrix(G1)): print(Matrix(G2)):

# G1:=	[8,10]	[9,11]	[6,15]	[1,16]
#	[5,13]	[10,14]	[16,12]	[4,5]
#	[14,9]	[15,4]	[11,1]	[2,8]
#	[13,2]	[7,7]	[12,3]	[3,6]

# G2:= 	[9,16] 	[21,19]	[14,13]	 [24,32] [25,10] [17,5]	[7,12]
#	[30,35]	[2,23] 	[34,28]	 [19,3]	 [8,17]	 [4,8]  [23,14]
#	[3,24] 	[29,6] 	[18,18]	 [12,34] [20,9]  [1,30] [27,2]
#	[5,33] 	[31,31]	[16,20]	 [13,11] [15,25] [6,1]  [10,7]
#	[28,27] [22,26]	[11,21]	 [32,29] [26,15] [35,4] [33,22]

#(a) Using G1:
# (i) find the outcome of the sequential version of G1 when Player Row goes first
# Option 1: Row chooses strategy R1, Column responds with strategy C4 for an outcome of 1-16
# Option 2: Row chooses strategy R2, Column responds with strategy C2 for an outcome of 10-14
# Option 3: Row chooses strategy R3, Column responds with strategy C1 for an outcome of 14-9
# Option 4: Row chooses strategy R4, Column responds with strategy C2 for an outcome of 7-7
# So Row chooses strategy R3 which maximizes Row's points, and row wins with strategy [3,1] and outcome [14,9]



# (ii) find the outcome of the sequential version of G1 when Player Column goes first
# Option 1: Column chooses strategy C1, Row responds with strategy R3 for an outcome of 14-9
# Option 2: Column chooses strategy C2, Row responds with strategy R3 for an outcome of 15-4
# Option 3: Column chooses strategy C3, Row responds with strategy R2 for an outcome of 16-12
# Option 4: Column chooses strategy C4, Row responds with strategy R2 for an outcome of 4-5
# So Column chooses strategy C3 which maximizes Column's points, but row wins with strategy [2,3] and outcome [16,12]

Here a better strategy for C would be C4, this is the only choice in which column wins. 
Further, maximizing the differences {9-14, 4-15, 12-16, 5-4} = {-5, -11, -4, 1} would give us this strategy!