Lesson DF5-DF6
DF5-DF6 Optimal mixed strategies and linear programming Quiz: AQA Further Maths, Unit 5
20 questions
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Lesson DF5-DF6, Optimal mixed strategies and linear programming: 20 multiple choice questions for the AQA Further Maths (7367), Unit 5: Optional application 3: discrete mathematics, written with Revision Ninja.
Host it live on the board and students join with a game code on their own devices, or revise alone with Free Play. The answers are revealed in the game.
The 20 questions
-
What defines a mixed strategy in game theory?
- Probability distribution
- Deterministic choice
- Pay-off matrix
- Saddle point
-
What does an optimal mixed strategy maximise for the row player?
- Guaranteed expected payoff
- Total matrix sum
- Maximum possible payoff
- Minimum opponent score
-
For a $2 \times n$ game, which point on the lower envelope gives the row player's optimal mix?
- Y-intercept
- Highest point
- Lowest point
- Origin
-
A zero-sum game has pay-off matrix (gains to the row player A) with rows A1: 1 3; A2: 4 2, and columns B1, B2. What is the value of this game?
- 3
- 2.5
- 2
- 3.5
-
A zero-sum game has pay-off matrix (gains to the row player A) with rows A1: 1 3; A2: 4 2, and columns B1, B2. What probability should the row player assign to A1 in an optimal mixed strategy?
- 0.4
- 0.25
- 0.5
- 0.75
-
A zero-sum game has pay-off matrix (gains to the row player A) with rows A1: 4 0 3; A2: 1 3 2, and columns B1, B2, B3. What is the value of this game?
- 1.5
- 2.25
- 2
- 3
-
In a game with rows (4, 0, 3) and (1, 3, 2), what probability should row 1 have?
- 1/2
- 2/3
- 1/4
- 1/3
-
In a game with rows (4, 0, 3) and (1, 3, 2), which columns form the optimal mix?
- B2 and B3
- B1 and B3
- All three columns
- B1 and B2
-
A zero-sum game has pay-off matrix (gains to the row player A) with rows A1: 4 0 3; A2: 1 3 2, and columns B1, B2, B3. In an optimal mixed strategy for the column player, what probability is assigned to column B1?
- 1/3
- 0.5
- 2/3
- 0.25
-
In a linear programme for a zero-sum game, what does the row player maximise?
- Sum of probabilities
- Column player loss
- Maximum entry value
- Guaranteed payoff v
-
What must the sum of probabilities in any mixed strategy equal?
- Number of rows
- 1
- 0
- Payoff value v
-
How many payoff constraints does a $3 \times 3$ zero-sum game linear programme have for the row player?
- 1
- 2
- 3
- 9
-
If a zero-sum game contains a saddle point, what type are its optimal strategies?
- Pure strategies
- Dominant columns
- Mixed strategies
- Infinite strategies
-
A zero-sum game has pay-off matrix (gains to the row player A) with rows A1: 3 -1; A2: -2 4, and columns B1, B2. In an optimal mixed strategy for the column player, what probability does B1 receive?
- 0.4
- 0.5
- 0.3
- 0.6
-
Which theorem states that maximin and minimax values are equal in mixed strategy games?
- Minimax theorem
- Fundamental theorem
- Bayes' theorem
- Central limit theorem
-
A calculated strategy probability is $p = 1.2$. Why is this result invalid?
- Negative probability
- Equals zero
- Exceeds maximum 1
- Must be integer
-
In the graphical method for a 2 x n game, where is the optimal mix found?
- Lowest upper envelope
- Maximum gradient point
- Highest lower envelope
- Intersection of all lines
-
Why is a row assigned a probability of zero in an optimal mixed strategy?
- Highest payoff row
- Sum exceeds one
- Equals total value
- Dominated or unneeded
-
A zero-sum game has pay-off matrix (gains to the row player A) with rows A1: 1 3; A2: 4 2, and columns B1, B2. If the row player uses A1 with probability 0.25 and A2 with probability 0.75, what is the expected payoff against column B1?
- 2.75
- 2.5
- 3.75
- 3.25
-
In an optimal mixed strategy, what property do the opponent's used pure strategies share?
- Equal expected payoff
- Equal probability
- Zero payoff sum
- Equal maximum payoff
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