Introduction to game theory

GAME THEORY

Presented by:

Mohamed Youssef Selim

Game Theory

It is a study of how to mathematically determine the best strategy for given conditions in order to optimize the outcome.

Game Theory

Game theoretic notions go back thousands of years– Talmud and Sun Tzu's writings.

Modern theory credited to John von Neumann and Oskar Morgenstern 1944.– Theory of Games and Economic Behavior. In the

early 1950s, John Nash (“A Beautiful Mind” fame)

generalized these results and provided the basis of the modern field.

Game Theory

John Nash (“A Beautiful Mind” fame) generalized these results and provided the basis of the modern field.

His film called Beautiful Mind “2001” Just google it “watch beautiful mind online”

Why is game theory important? All intelligent beings make decisions all the time. AI needs to perform these tasks as a result. Helps us to analyze situations more rationally and

formulate an acceptable alternative with respect to circumstance.

Useful in modeling strategic decision-making– Games against opponents– Games against "nature„

Provides structured insight into the value of information

Game Theory in the Real World Economists

innovated antitrust policy auctions of radio spectrum licenses for cell phone program that matches medical residents to hospitals.

Computer scientists new software algorithms and routing protocols Game AI

Military strategists nuclear policy and notions of strategic deterrence.

Sports coaching staffs run versus pass or pitch fast balls versus sliders.

Biologists what species have the greatest likelihood of extinction.

Other computer science applications Internet Routing Job scheduling Competition in client-server systems Peer-to-peer systems Cryptology Network security Sensor networks Game programming

7

What is a Game?

A game consists of–a set of players–a set of strategies for each player– the payoffs to each player for every

possible list of strategy choices by the players.

Types of Games

Sequential vs. Simultaneous moves Single Play vs. Iterated Zero vs. non-zero sum Perfect vs. Imperfect information Cooperative vs. conflict

RationalityAssumptions: humans are rational beings humans always seek the best

alternative in a set of possible choices

Why assume rationality? narrow down the range of

possibilities predictability

An Example of a Two-Player Game The players are called A and B. Player A has two strategies, called

“Up” and “Down”. Player B has two strategies, called

“Left” and “Right”. The table showing the payoffs to

both players for each of the four possible strategy combinations is the game’s payoff matrix.

An Example of a Two-Player Game

This is thegame’spayoff matrix.

Player B

Player A

Player A’s payoff is shown first.Player B’s payoff is shown second.

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


E.g. if A plays Up and B plays Right then A’s payoff is 1 and B’s payoff is 8.


Player B

Player A

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


And if A plays Down and B plays Right then A’s payoff is 2 and B’s payoff is 1.


Player B

Player A

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)

An Example of a Two-Player GamePlayer B

Player A

A play of the game is a pair such as (U,R)where the 1st element is the strategychosen by Player A and the 2nd is the strategy chosen by Player B.

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


What plays are we likely to see for thisgame?

Player B

Player A

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player AIs (U,R) alikely play?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player A

If B plays Right then A’s best reply is Downsince this improves A’s payoff from 1 to 2.So (U,R) is not a likely play.

Is (U,R) alikely play?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player AIs (D,R) alikely play?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player AIs (D,R) alikely play?

If B plays Right then A’s best reply is Down.

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player A

If B plays Right then A’s best reply is Down.If A plays Down then B’s best reply is Right.So (D,R) is a likely play.

Is (D,R) alikely play?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player AIs (D,L) alikely play?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player A

If A plays Down then B’s best reply is Right,so (D,L) is not a likely play.

Is (D,L) alikely play?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player AIs (U,L) alikely play?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player A

If A plays Up then B’s best reply is Left.

Is (U,L) alikely play?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player A

If A plays Up then B’s best reply is Left.If B plays Left then A’s best reply is Up.So (U,L) is a likely play.

Is (U,L) alikely play?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)

Nash Equilibrium

A play of the game where each strategy is a best reply to the other is a Nash equilibrium.

Our example has two Nash equilibria; (U,L) and (D,R).


Player A

(U,L) and (D,R) are both Nash equilibria forthe game.

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player A

(U,L) and (D,R) are both Nash equilibria forthe game. But which will we see? Noticethat (U,L) is preferred to (D,R) by bothplayers. Must we then see (U,L) only?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)

The Prisoner’s Dilemma

To see if Pareto-preferred outcomes must be what we see in the play of a game, consider a famous second example of a two-player game called the Prisoner’s Dilemma.


What plays are we likely to see for thisgame?

Clyde

Bonnie(-5,-5) (-30,-1)

(-1,-30) (-10,-10)

S

C

S C


If Bonnie plays Silence then Clyde’s bestreply is Confess.

Clyde

Bonnie(-5,-5) (-30,-1)

(-1,-30) (-10,-10)

S

C

S C


If Bonnie plays Silence then Clyde’s bestreply is Confess.If Bonnie plays Confess then Clyde’sbest reply is Confess.

Clyde

Bonnie(-5,-5) (-30,-1)

(-1,-30) (-10,-10)

S

C

S C


So no matter what Bonnie plays, Clyde’sbest reply is always Confess.Confess is a dominant strategy for Clyde.

Clyde

Bonnie(-5,-5) (-30,-1)

(-1,-30) (-10,-10)

S

C

S C


Similarly, no matter what Clyde plays,Bonnie’s best reply is always Confess.Confess is a dominant strategy forBonnie also.

Clyde

Bonnie(-5,-5) (-30,-1)

(-1,-30) (-10,-10)

S

C

S C


So the only Nash equilibrium for thisgame is (C,C), even though (S,S) givesboth Bonnie and Clyde better payoffs.The only Nash equilibrium is inefficient.

Clyde

Bonnie(-5,-5) (-30,-1)

(-1,-30) (-10,-10)

S

C

S C

Who Plays When?

In both examples the players chose their strategies simultaneously.

Such games are simultaneous play games.

Who Plays When?

But there are games in which one player plays before another player.

Such games are sequential play games.

The player who plays first is the leader. The player who plays second is the follower.

A Sequential Game Example

Sometimes a game has more than one Nash equilibrium and it is hard to say which is more likely to occur.

When such a game is sequential it is sometimes possible to argue that one of the Nash equilibria is more likely to occur than the other.

A Sequential Game ExamplePlayer B

Player A

(U,L) and (D,R) are both Nash equilibriawhen this game is played simultaneouslyand we have no way of deciding whichequilibrium is more likely to occur.

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)

A Sequential Game ExamplePlayer B

Player A

Suppose instead that the game is playedsequentially, with A leading and B following.We can rewrite the game in its extensive form.

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


U D

L LR R

(3,9) (1,8) (0,0) (2,1)

A

B BA plays first.B plays second.


U D

L LR R

(3,9) (1,8) (0,0) (2,1)

A


(U,L) is a Nash equilibrium.


U D

L LR R

(3,9) (1,8) (0,0) (2,1)

A


(U,L) is a Nash equilibrium.(D,R) is a Nash equilibrium.Which is more likely to occur?


U D

L LR R

(3,9) (1,8) (0,0) (2,1)

A


If A plays U then B plays L; A gets 3.


U D

L LR R

(3,9) (1,8) (0,0) (2,1)

A


If A plays U then B plays L; A gets 3.If A plays D then B plays R; A gets 2.


U D

L LR R

(3,9) (1,8) (0,0) (2,1)

A


If A plays U then B plays L; A gets 3.If A plays D then B plays R; A gets 2.So (U,L) is the likely Nash equilibrium.

Pure StrategiesPlayer B

Player A

This is our original example once more.Suppose again that play is simultaneous.We discovered that the game has two Nashequilibria; (U,L) and (D,R).

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player A

Player A’s has been thought of as choosingto play either U or D, but no combination ofboth; that is, as playing purely U or D.U and D are Player A’s pure strategies.

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player A

Similarly, L and R are Player B’s purestrategies.

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player A

Consequently, (U,L) and (D,R) are purestrategy Nash equilibria. Must every gamehave at least one pure strategy Nashequilibrium?

L R

U

D

(3,9)

(0,0)

(1,8)

(2,1)


Player A

Here is a new game. Are there any purestrategy Nash equilibria?

(1,2) (0,4)

(0,5) (3,2)

U

D

L R


Player A

Is (U,L) a Nash equilibrium?

(1,2) (0,4)

(0,5) (3,2)

U

D

L R


Player A

Is (U,L) a Nash equilibrium? No.Is (U,R) a Nash equilibrium?

(1,2) (0,4)

(0,5) (3,2)

U

D

L R


Player A

Is (U,L) a Nash equilibrium? No.Is (U,R) a Nash equilibrium? No.Is (D,L) a Nash equilibrium?

(1,2) (0,4)

(0,5) (3,2)

U

D

L R


Player A

Is (U,L) a Nash equilibrium? No.Is (U,R) a Nash equilibrium? No.Is (D,L) a Nash equilibrium? No.Is (D,R) a Nash equilibrium?

(1,2) (0,4)

(0,5) (3,2)

U

D

L R


Player A

Is (U,L) a Nash equilibrium? No.Is (U,R) a Nash equilibrium? No.Is (D,L) a Nash equilibrium? No.Is (D,R) a Nash equilibrium? No.

(1,2) (0,4)

(0,5) (3,2)

U

D

L R


Player A

So the game has no Nash equilibria in purestrategies. Even so, the game does have aNash equilibrium, but in mixed strategies.

(1,2) (0,4)

(0,5) (3,2)

U

D

L R

Mixed Strategies

Instead of playing purely Up or Down, Player A selects a probability distribution (pU,1-pU), meaning that with probability pU Player A will play Up and with probability 1-pU will play Down.

Player A is mixing over the pure strategies Up and Down.

The probability distribution (pU,1-pU) is a mixed strategy for Player A.

Mixed Strategies

Similarly, Player B selects a probability distribution (pL,1-pL), meaning that with probability pL Player B will play Left and with probability 1-pL will play Right.

Player B is mixing over the pure strategies Left and Right.

The probability distribution (pL,1-pL) is a mixed strategy for Player B.

Mixed Strategies

Player A

This game has no pure strategy Nash equilibria but it does have a Nash equilibrium in mixed strategies. How is itcomputed?

(1,2) (0,4)

(0,5) (3,2)

U

D

L RPlayer B

Mixed Strategies

Player A(1,2) (0,4)

(0,5) (3,2)

U,pU

D,1-pU

L,pL R,1-pL

Player B

Mixed Strategies

Player A

If B plays Left her expected payoff is2 5 1p pU U ( )

(1,2) (0,4)

(0,5) (3,2)

U,pU

D,1-pU

L,pL R,1-pL

Player B

Mixed Strategies

Player A

If B plays Left her expected payoff is

If B plays Right her expected payoff is2 5 1p pU U ( ).

4 2 1p pU U ( ).

(1,2) (0,4)

(0,5) (3,2)

U,pU

D,1-pU

L,pL R,1-pL

Player B

Mixed Strategies

Player A

2 5 1 4 2 1p p p pU U U U ( ) ( )If thenB would play only Left. But there are noNash equilibria in which B plays only Left.

(1,2) (0,4)

(0,5) (3,2)

U,pU

D,1-pU

L,pL R,1-pL

Player B

Mixed Strategies

Player A

2 5 1 4 2 1p p p pU U U U ( ) ( )If thenB would play only Right. But there are noNash equilibria in which B plays only Right.

(1,2) (0,4)

(0,5) (3,2)

U,pU

D,1-pU

L,pL R,1-pL

Player B

Mixed Strategies

Player A

So for there to exist a Nash equilibrium, Bmust be indifferent between playing Left orRight; i.e.

(1,2) (0,4)

(0,5) (3,2)

U,pU

D,1-pU

L,pL R,1-pL

2 5 1 4 2 1p p p pU U U U ( ) ( )

Player B

Mixed Strategies

Player A

So for there to exist a Nash equilibrium, Bmust be indifferent between playing Left orRight; i.e. 2 5 1 4 2 1

3 5p p p p

pU U U U

U

( ) ( )

/ .

(1,2) (0,4)

(0,5) (3,2)

U,pU

D,1-pU

L,pL R,1-pL

Player B

Mixed Strategies

Player A

So for there to exist a Nash equilibrium, Bmust be indifferent between playing Left orRight; i.e. 2 5 1 4 2 1

3 5p p p p

pU U U U

U

( ) ( )

/ .

(1,2) (0,4)

(0,5) (3,2)

U,

D,

L,pL R,1-pL

53

52

Player B

Mixed Strategies

Player A(1,2) (0,4)

(0,5) (3,2)

L,pL R,1-pL

U,

D,53

52

Player B

Mixed Strategies

Player A

If A plays Up his expected payoff is.)1(01 LLL ppp

(1,2) (0,4)

(0,5) (3,2)

L,pL R,1-pL

U,

D,53

52

Player B

Mixed Strategies

Player A

If A plays Up his expected payoff is

If A plays Down his expected payoff is).1(3)1(30 LLL ppp

(1,2) (0,4)

(0,5) (3,2)

L,pL R,1-pL

U,

D,53

52

.)1(01 LLL ppp

Player B

Mixed Strategies

Player A

p pL L 3 1( )If then A would play only Up.But there are no Nash equilibria in which Aplays only Up.

(1,2) (0,4)

(0,5) (3,2)

L,pL R,1-pL

U,

D,53

52

Player B

Mixed Strategies

Player A

IfDown. But there are no Nash equilibria inwhich A plays only Down.

p pL L 3 1( ) then A would play only

(1,2) (0,4)

(0,5) (3,2)

L,pL R,1-pL

U,

D,53

52

Player B

Mixed Strategies

Player A

So for there to exist a Nash equilibrium, Amust be indifferent between playing Up orDown; i.e. p pL L 3 1( )

(1,2) (0,4)

(0,5) (3,2)

L,pL R,1-pL

U,

D,53

52

Player B

Mixed Strategies

Player A

So for there to exist a Nash equilibrium, Amust be indifferent between playing Up orDown; i.e. p p pL L L 3 1 3 4( ) / .

(1,2) (0,4)

(0,5) (3,2)

L,pL R,1-pL

U,

D,53

52

Player B

Mixed Strategies

Player A

So for there to exist a Nash equilibrium, Amust be indifferent between playing Up orDown; i.e. p p pL L L 3 1 3 4( ) / .

(1,2) (0,4)

(0,5) (3,2)

L, R,

U,

D,53

52

43

41

Player B

Mixed StrategiesPlayer B

Player A(0,4)U,

D,

L, R,43

41

53

52

(1,2)9/20 3/20(0,5) (3,2)6/20 2/20

Limitations & Problems

Assumes players always maximize their outcomes

Some outcomes are difficult to provide a utility for

Not all of the payoffs can be quantified

Not applicable to all problems

Summary What is game theory?

– Abstraction modeling multi-person interactions

How is game theory applied?– Payoff matrix contains each person’s utilities

for various strategies Who uses game theory?

– Economists, Ecologists, Network people,... How is this related to AI?

– Provides a method to simulate a thinking agent

Sources Much more available on the web. These slides (with changes and additions) adapted

from: http://pages.cpsc.ucalgary.ca/~jacob/Courses/Winter2000/CPSC533/Pages/index.html

Three interesting classics:– John von Neumann & Oskar Morgenstern, Theory of

Games & Economic Behavior (Princeton, 1944).– John McDonald, Strategy in Poker, Business & War

(Norton, 1950)– Oskar Morgenstern, "The Theory of Games,"

Scientific American, May 1949; translated as "Theorie des Spiels," Die Amerikanische Rundschau, August 1949.

http://pages.cpsc.ucalgary.ca/~jacob/Courses/Winter2000/CPSC533/Pages/index.html

http://pages.cpsc.ucalgary.ca/~jacob/Courses/Winter2000/CPSC533/Pages/index.html

Engineering

Introduction to game theory