The Player class

The features of the agents are defined within class Player: the prior Gaussian distribution characterized by the mean (mu) and the standard deviation (sigma), the standard deviation of the performance (beta), and the dynamic uncertainty of the skill (gamma).

The default value of MU = 0.0, SIGMA = 6.0, BETA = 1.0, GAMMA = 0.03

>>> a1 = ttt.Player()
>>> a1
Player(Gaussian(mu=0.000, sigma=6.000), beta=1.000, gamma=0.030)
>>> a2 = ttt.Player(ttt.Gaussian(0.0, 1.0))
>>> a2
Player(Gaussian(mu=0.000, sigma=6.000), beta=1.000, gamma=0.030)

We can also create special players who have non-random performances beta = 0.0, and whose skills do not change over time gamma=0.0.

>>> a3 = ttt.Player(beta=0.0, gamma=0.0)
>>> a3.beta
0.0
>>> a3.gamma
0.0

Performance

The performances p are random variables around their unknown true skill s,

\(p \sim \mathcal{N}(s,\beta^2)\)

>>> a2.performance()
N(mu=0.000, sigma=1.414)
>>> a3.performance()
N(mu=0.000, sigma=6.000)