01 Strategies and utilities¶
Corresponding chapters¶
Objectives¶
- Define mixed strategies
- Understand utility calculation for mixed strategies
- Understand utility calculation as a linear algebraic construct
- Be able to identify dominated strategies
- Understand notion of Common knowledge of granularity
Notes¶
Utility calculations¶
Use matching pennies
form
have students play in pairs.
Following each game:
- Ask how many people won?
- Ask why they won?
Mixed strategies¶
Look at definition for mixed strategies.
Consider:
Let us assume we have \(\sigma_r=(.3, .7)\) and \(\sigma_c=(.1, .9)\):
because the game is zero sum we immediately know:
This corresponds to the linear algebraic multiplication:
(Go through this on the board, make sure students are comfortable.)
This can be done straightforwardly using numpy
:
>>> import numpy as np
>>> A = np.array([[2, -2], [-1, 1]])
>>> B = np.array([[-2, 2], [1, -1]])
>>> sigma_r = np.array([.3, .7])
>>> sigma_c = np.array([.1, .9])
>>> np.dot(sigma_r, np.dot(A, sigma_c)), np.dot(sigma_r, np.dot(B, sigma_c))
(0.079..., -0.079...)
Strategy profiles as coordinates on a game¶
One way to thing of any game \((A, B)\in{\mathbb{R}^{m \times n}}^2\) is as a mapping from the set of strategies \([0,1]_{\mathbb{R}}^{m}\times [0,1]_{\mathbb{R}}^{m}\) to \(\mathbb{R}^2\): the utility space.
Equivalently, if \(S_r, S_c\) are the strategy spaces of the row/column player:
We can use games defined in nashpy
in that way:
>>> import nash
>>> game = nash.Game(A, B)
>>> game[sigma_r, sigma_c]
array([ 0.08, -0.08])
Rationalisation of strategies¶
Identify two volunteers and play a sequence of zero sum games where they play as a team against me. The group is the row player.
(No dominated strategy)
(First column weakly dominates second column)
(First row strictly dominates second row) (Second column strictly dominates first column)
(First row weakly dominates second row) (First column weakly dominates second column)
(First row dominates second row) (First column dominates second column)
Now pit the two players against each other, the utilities represent the share of the total amount of chocolates/sweets gathered so far:
Capture all of the above (on the white board) and discuss each action and why they were taken.
Iterated elimination of dominated strategies¶
As a class work through the following example.
First row dominates second row
\[\begin{split}A = \begin{pmatrix} 2 & 5 \\ 7 & 3 \end{pmatrix}\qquad B = \begin{pmatrix} 0 & 3 \\ 0 & 1 \end{pmatrix}\end{split}\]Second column dominates first column
\[\begin{split}A = \begin{pmatrix} 2\\ 7 \end{pmatrix}\qquad B = \begin{pmatrix} 0\\ 0 \end{pmatrix}\end{split}\]Second (third) row dominates first row. Thus the rationalised behaviour is \((r_3, c_1)\).
Now return to the last example played as a pair:
The first row/column weakly dominate the second row/column:
\[\begin{split}A = \begin{pmatrix} -1 & 1 \\ 1 & -1 \end{pmatrix}\qquad B = \begin{pmatrix} 1 & -1 \\ -1 & 1 \end{pmatrix}\end{split}\]
There is nothing further that we can do here.