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# Mixed Strategy

📗 A mixed strategy is when a player randomizes between multiple actions: Wikipedia.
📗 A pure strategy is when a player uses only one action with probability 1.
📗 A mixed strategy Nash equilibrium is a Nash equilibrium for the game in which mixed strategies are allowed (called mixed extension of the original game).
➩ If the mixed strategies are mutual best responses, then they form a mixed strategy Nash equilibrium (see Math Note for the mathematical definition).
Math Note
📗 For a two-player general-sum game with rewards \(r\) (both players are maximizing), an action profile \(\left(a_{1}, a_{2}\right)\) is a pure strategy Nash equilibrium if \(r_{1}\left(a_{1}, a_{2}\right) \geq r_{1}\left(a', a_{2}\right)\) for every \(a'\) valid action of player \(1\); and \(r_{2}\left(a_{1}, a_{2}\right) \geq r_{2}\left(a_{1}, a'\right)\) for every \(a'\) valid action of player \(2\). 
📗 An mixed strategy profile \(\left(\pi_{1}, \pi_{2}\right)\), where \(\pi_{i}\left(a\right)\) is the probability that player \(i\) chooses action \(a\), is a mixed strategy Nash equilibrium if \(\mathbb{E}\left[r_{1}\left(\pi_{1}, \pi_{2}\right)\right] \geq \mathbb{E}\left[r_{1}\left(\pi', \pi_{2}\right)\right]\) for every \(\pi'\) mixed strategy of player \(1\); and if \(\mathbb{E}\left[r_{2}\left(\pi_{1}, \pi_{2}\right)\right] \geq \mathbb{E}\left[r_{2}\left(\pi_{1}, \pi'\right)\right]\) for every \(\pi'\) mixed strategy of player \(2\).
➩ Here, the expectation is over the randomness of the mixed strategies, or \(\mathbb{E}\left[r_{i}\left(\pi_{1}, \pi_{2}\right)\right] = \displaystyle\sum_{a_{1}, a_{2}} r_{i}\left(a_{1}, a_{2}\right) \pi_{1}\left(a_{1}\right) \pi_{2}\left(a_{2}\right)\), where the sum is over all valid \(\left(a_{1}, a_{2}\right)\) actions of players \(1\) and \(2\).
➩ This condition is usually difficult to check: another equivalent condition is: \(\left(\pi_{1}, \pi_{2}\right)\) is a mixed strategy Nash equilibrium if \(\mathbb{E}\left[r_{1}\left(\pi_{1}, \pi_{2}\right)\right] \geq \mathbb{E}\left[r_{1}\left(a', \pi_{2}\right)\right]\) for every \(a'\) valid action of player \(1\); and if \(\mathbb{E}\left[r_{2}\left(\pi_{1}, \pi_{2}\right)\right] \geq \mathbb{E}\left[r_{2}\left(\pi_{1}, a'\right)\right]\) for every \(a'\) valid action of player \(2\).
Example
📗 For rock paper scissor game, there is no pure Nash equilibrium, but there is one mixed Nash equilibrium where every player uses each action with probability \(\dfrac{1}{3}\): Link.
📗 The game matrix is:
\(a_{1} \setminus a_{2}\) Rock Paper Scissors
Rock \(0\) \(-1\) \(1\)
Paper \(1\) \(0\) \(-1\)
Scissors \(-1\) \(1\) \(0\)

Nash Equilibrium:
[Note] Use the space to explain the steps or just take notes:

[Q1]
 
In-class Quiz ID:
📗 [4 points] Given the following game payoff table, suppose the row player uses a pure strategy, and column player uses a mixed strategy playing L with probability \(q\). What is the smallest and largest value of \(q\) in a mixed strategy Nash equilibrium?
Row \ Col L R
U
D

Note: the following is a diagram of the best responses (make sure you understand what they are and how to draw them). The red curve is the best response for the column player and the blue curve is the best response for the row player.

📗 Answer (comma separated vector): .
[Note] Use the space to explain the steps or just take notes:

[Q2]
 
In-class Quiz ID:
📗 [4 points] Given the following BoS (Battle of Sexes) game, what is the row (Romeo) player's (expected) value (i.e. payoff) in the mixed strategy Nash equilibrium?
Romeo \ Juliet Bach Stravinsky
Bach
Stravinsky

📗 Answer: .
[Note] Use the space to explain the steps or just take notes:

[Q3]
 
Example
📗 Run vs Pass game: YouTube.



# Nash Theorem

📗 Every finite game has a (possibly mixed) Nash equilibrium: Wikipedia.




# Questions?

📗 If you have questions, please use (i) Zoom chat, (ii) Piazza: Link, (iii) Office hours and discussion sessions. Please do NOT use Canvas mail and use email only to the course instructor (not TAs) for grading issues.
Additional In-class Discussion
📗 Sometimes a question not in the notes will be asked during the lecture, you can submit your answer here:

Notes (not visible to other students):
[Q4]

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Additional In-class Quiz
📗 Sometimes a question not in the notes will be asked during the lecture, you can submit your answer here:
A.
B.
C.
D.
E.
Notes (not visible to other students):
[Q5]

Submit your answer to see other students answers (click the submit button to refresh): 






# In-class Quiz Instructions

📗 To get full points on the in-class quizzes for a lecture:
➩ Submit relevant answers to the questions discussed during the lecture: incorrect answers are okay.
➩ Some questions require [notes] to earn the point.
➩ Some questions require special ID (given during the lecture) to earn the point.
➩ Do not submit answers to questions that are not discussed during the lectures. Each such submission will result in a deduction of one point.
➩ Submissions after the lecture, before the midterm (first 14 lectures) and the final exam (last 14 lectures), are accepted. After the exams, no in-class quiz submissions will be accepted.
➩ The grade on Canvas Assignment Q21 is computed as number of points divided by the number of questions asked (out of 1) and updated on Canvas every weekend.
📗 If there are any issues with submission on the website, please use this Google form: Link.
📗 Bonus point opportunities during a few lectures (added to in-class quiz above 20 points).
📗 Notes and code adapted from the course taught by Professors Jerry Zhu, Blerina Gkotse, Yudong Chen, Yingyu Liang, Charles Dyer. Some content are generated using Copilot .

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Last Updated: August 17, 2026 at 1:53 AM