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Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

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The Essentials of a Game 4. Information: What players know (believe) when choosing actions. Perfect Information: Players know their own payoffs other player(s) payoffs the history of the game, including other(s) current action* *Actions are sequential (e.g., chess, tic-tac-toe). Common Knowledge

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Page 1: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Zero-sum Games

• The Essentials of a Game• Extensive Game• Matrix Game• Dominant Strategies• Prudent Strategies• Solving the Zero-sum Game• The Minimax Theorem

Page 2: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

The Essentials of a Game1. Players: We require at least 2 players (Players choose actions

and receive payoffs.)

2. Actions: Player i chooses from a finite set of actions, S = {s1,s2,…..,sn}. Player j chooses from a finite set of actions T = {t1,t2,……,tm}.

3. Payoffs: We define Pi(s,t) as the payoff to player i, if Player i chooses s and player j chooses t. We require that Pi(s,t) + Pj(s,t) = 0 for all combinations of s and t.

4. Information: What players know (believe) when choosing actions.

ZERO-SUM

Page 3: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

The Essentials of a Game

4. Information: What players know (believe) when choosing actions.

Perfect Information: Players know

• their own payoffs • other player(s) payoffs • the history of the game, including other(s) current action*

*Actions are sequential (e.g., chess, tic-tac-toe).

Common Knowledge

Page 4: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Extensive GamePlayer 1 chooses a = {1, 2 or 3} Player 2 b = {1 or 2} Player 1 c = {1, 2 or 3}

Payoffs = a2 + b2 + c2 if /4 leaves remainder of 0 or 1. -(a2 + b2 + c2) if /4 leaves remainder of 2 or 3. Player1’sdecision nodes

-3 -6 -11 -6 9 -14 -6 9 -14 9 12 17 -11 -14 -19 -14 17 -22GAME 1.

“Square the Diagonal”(Rapoport: 48-9)

Player 2’sdecision nodes

1 32

1 21

23

Page 5: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Extensive GameHow should the game be played?Solution: a set of “advisable” strategies, one for each player.Strategy: a complete plan of action for every possible decision

node of the game, including nodes that could only be reached by a mistake at an earlier node.

Player1‘s advisable Strategy in red

-3 -6 -11 -6 9 -14 -6 9 -14 9 12 17 -11 -14 -19 -14 17 -22GAME 1.

1 32

1 21

23

Start at the final decision nodes (in red) Backwards-induction

Page 6: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Extensive GameHow should the game be played?Solution: a set of “advisable” strategies, one for each player.Strategy: a complete plan of action for every possible decision

node of the game, including nodes that could only be reached by a mistake at an earlier node.

Player1‘s advisable Strategy in red

-3 -6 -11 -6 9 -14 -6 9 -14 9 12 17 -11 -14 -19 -14 17 -22GAME 1.

Player2’s advisable strategy in green

1 32

1 21

23

Player1’s advisable strategy in red

Page 7: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Extensive GameHow should the game be played?If both player’s choose their advisable (prudent) strategies, Player1 will start with 2, Player2 will choose 1, then Player1 will choose 2. The outcome will be 9 for Player1 (-9 for Player2). If a player makes a mistake, or deviates, her payoff will be less.

-3 -6 -11 -6 9 -14 -6 9 -14 9 12 17 -11 -14 -19 -14 17 -22GAME 1.

1 32

1 21

23

Page 8: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Extensive GameA Clarification: Rapoport (pp. 49-53) claims Player 1 has 27 strategies. However, if we consider inconsistent strategies, the actual number of strategies available to Player 1 is 37 = 2187.

An inconsistent strategy includes actions at decision nodes that would not be reached by correct implementation at earlier nodes, i.e., could only be reached by mistake.

Since we can think of a strategy as a set of instructions (or program) given to an agent or referee (or machine) to implement, a complete strategy must include instructions for what to do after a mistake is made. This greatly expands the number of strategies available, though the essence of Rapoport’s analysis is correct.

Page 9: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Extensive GameComplete Information: Players know their own payoffs;

other player(s) payoffs; history of the game excluding other(s) current action*

*Actions are simultaneous

-3 -6 -11 -6 9 -14 -6 9 -14 9 12 17 -11 -14 -19 -14 17 -22GAME 1.

1 32

1 21

23

Information Sets

Page 10: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Matrix Game

-3 -6-6 9

-11 -14-6 99 12

-14 17-11 -14-14 17-19 -22

T1 T2

Also called “Normal Form” or “Strategic Game”

Solution = {S22, T1}

S11

S12

S13

S21

S22

S23

S31

S32

S33

Page 11: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Dominant StrategiesDefinition

Dominant Strategy: a strategy that is best no matter what the opponent(s) choose(s).

T1 T2 T3 T1 T2 T3

-3 0 -10

-1 5 2

-2 -4 0

-3 0 1

-1 5 2

-2 2 0

S1

S2

S3

S1

S2

S3

Page 12: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Dominant StrategiesDefinition

Dominant Strategy: a strategy that is best no matter what the opponent(s) choose(s).

T1 T2 T3 T1 T2 T3

Sure Thing Principle: If you have a dominant strategy, use it!

-3 0 -10

-1 5 2

-2 -4 0

-3 0 1

-1 5 2

-2 2 0

S1

S2

S3

S1

S2

S3

Page 13: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Prudent Strategies

T1 T2 T3

Player 1’s worst payoffs for each strategy are in red.

-3 1 -20

-1 5 2

-2 -4 15

S1

S2

S3

Definitions

Prudent Strategy: A prudent strategy for player i maximizes the minimum payoff she can get from playing different strategies. Such a strategy is simply maxsmintP(s,t) for player i.

Page 14: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Prudent Strategies

T1 T2 T3

Player 2’s worst payoffs for each strategy are in green.

-3 1 -20

-1 5 2

-2 -4 15

S1

S2

S3

Definitions

Prudent Strategy: A prudent strategy for player i maximizes the minimum payoff she can get from playing different strategies. Such a strategy is simply maxsmintP(s,t) for player i.

Page 15: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Prudent Strategies

T1 T2 T3

-3 1 -20

-1 5 2

-2 -4 15

S1

S2

S3

Definitions

Prudent Strategy: A prudent strategy for player i maximizes the minimum payoff she can get from playing different strategies. Such a strategy is simply maxsmintP(s,t) for player i.

Saddlepoint: A set of prudent strategies (one for each player), s. t. (s’, t’) is a saddlepoint, iff maxmin = minmax.

We call the solution {S2, T1} a saddlepoint

Page 16: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Prudent Strategies

-3 1 -20

-1 5 2

-2 -4 15

S1

S2

S3

Saddlepoint: A set of prudent strategies (one for each player), s. t. (s’, t’) is a saddlepoint, iff

maxmin = minmax.

Page 17: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Mixed Strategies

Left Right

L R L R

-2 4 2 -1

Player 1

Player 2

GAME 2: Button-Button

Player 1 hides a button in his Left or Right hand.

Player 2 observes Player 1’s choice and then picks either Left or Right.

Draw the game in matrix form.

Page 18: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Mixed Strategies

Left Right

L R L R

-2 4 2 -1

Player 1

Player 2

GAME 2: Button-Button

Player 1 has 2 strategies;Player 2 has 4 strategies:

-2 4 -2 4

2 -1 -1 2

L

R

LL RR LR RL

Page 19: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Mixed Strategies

Left Right

L R L R

-2 4 2 -1

Player 1

Player 2

GAME 2: Button-Button

The game can be solve by backwards-induction. Player 2 will …

-2 4 -2 4

2 -1 -1 2

L

R

LL RR LR RL

Page 20: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Mixed Strategies

Left Right

L R L R

-2 4 2 -1

Player 1

Player 2

GAME 2: Button-Button

The game can be solve by backwards-induction. … therefore, Player 1 will:

-2 4 -2 4

2 -1 -1 2

L

R

LL RR LR RL

Page 21: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Mixed Strategies

Left Right

L R L R

-2 4 2 -1

Player 1

Player 2

-2 4

2 -1

L R

L

R

GAME 2: Button-Button

What would happen if Player 2 cannot observe Player 1’s choice?

Page 22: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Solving the Zero-sum Game

GAME 2.

-2 4

2 -1

Definition

Mixed Strategy: A mixed strategy for player i is a probability distribution over all strategies available to player i.

Let (p, 1-p) = prob. Player I chooses L, R.(q, 1-q) = prob. Player 2 chooses L, R.

L R

L

R

Page 23: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Solving the Zero-sum Game

GAME 2.

-2 4

2 -1

Then Player 1’s expected payoffs are: EP(L) = -2(p) + 2(1-p) = 2 – 4p EP(R) = 4(p) – 1(1-p) = 5p – 1

L R

L

R

(p)

(1-p)

(q) (1-q)0 1 p

EP(L) = 2 – 4p

EP(R) = 5p – 1

EP

p*=1/3

2

-1

4

-2

Page 24: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Solving the Zero-sum Game

GAME 2.

-2 4

2 -1

Player 2’s expected payoffs are:

EP(L) = 2(q) – 4(1-q) = 6q – 4 EP(R) = -2(q) + 1(1-q) = -3q + 1

EP(L) = EP(R) => q* = 5/9

L R

L

R

(p)

(1-p)

(q) (1-q)

Page 25: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Solving the Zero-sum GamePlayer 1

EP(L) = -2(p) + 2(1-p) = 2 – 4p EP(R) = 4(p) – 1(1-p) = 5p – 1

0 p 1 q

-EP2

p*=1/3

2

-1

4

-2

2/3 = EP1* = - EP2* =-2/3

This is the

Value

of the game.

EP1

-4

2

-2

2

q*= 5/9

Player 2

EP(L) = 2(q) – 4(1-q) = 6q – 4 EP(R) = -2(q) + 1(1-q) = -3q + 1

Page 26: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

Solving the Zero-sum Game

GAME 3.

-2 4

2 -1

Then Player 1’s expected payoffs are:

EP(T1) = -2(p) + 2(1-p) EP(T2) = 4(p) – 1(1-p)

EP(T1) = EP(T2) => p* = 1/3

And Player 2’s expected payoffs are:

(V)alue = 2/3

L R

L

R

(p)

(1-p)

(q) (1-q)

(Security) Value: the expected payoff when both (all) players play prudent strategies.

Any deviation by an opponent leads to an equal or greater payoff.

Page 27: Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem

The Minimax Theorem

Von Neumann (1928)

Every zero sum game has a saddlepoint (in pure or mixed strategies), s.t., there exists a unique value, i.e., an outcome of the game where

maxmin = minmax.