Compute expected utilities for the k-rationalizability model

[A-Lounsbury]

Written in computeKMatrix function. Needs to be tested, but first need some way of printing them out. Maybe we need EU as a SimGame attribute?

[A-Lounsbury]

Received

EU[x] += curList.getListNode(x).payoff * self.outcomeProbabilities[num]
IndexError: list index out of range

Need to compute outcomeProbabilities somewhere; although, it appears we did that in probabilizeKChoices.

[A-Lounsbury]

Still resulting in [0.0, 0.0].

[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)

which has the correct expected utilities.