Fix outcome probabilities for the k-rationalizability model

[A-Lounsbury]

This test

krmodel = [
    [
        [[2, 12], [5, 6], [9, 0]],
        [[0, 24], [19, 5], [10, 10]],
        [[1, 3], [7, 5], [5, 25]],
    ]
]

G = SimGame(2)
G.enterData(2, [3, 3], krmodel)
G.print()
print()
G.printKMatrix(probabilities=[0.1, 0.4, 0.4, 0.1])

results in

P(1, 2) = 0.10000000000000002
P(1, 0) = 0.9000000000000002
P(0, 2) = 0.10000000000000003
P(0, 0) = 0.9000000000000004
EU_0 = 1.8500000000000005
EU_1 = 16.700000000000003
(1, 2) (1, 0) (1, 0) (1, 0)
(1, 2) (1, 0) (1, 0) (1, 0)
(0, 2) (0, 0) (0, 0) (0, 0)
(0, 2) (0, 0) (0, 0) (0, 0)

while the expected result is

P(1, 2) = 0.05
P(1, 0) = 0.45
P(0, 2) = 0.05
P(0, 0) = 0.45

[A-Lounsbury]

It is very strange that the expected utilities are correct while the outcome probabilities are not. I really have no clue how that's happening.

[A-Lounsbury]

Instead of clearing self.oucomeProbabilities with self.outcomeProbabilities = [0.0 for n in range(len(self.kOutcomes))], we were simply appending more 0.0s.