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The Candidate-Voter Model Recall the Candidate-Voter Model: I Have a political spectrum (0 - 100)

Math 180 - Game Theory - Penn Math

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Page 1: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

Recall the Candidate-Voter Model:

I Have a political spectrum (0− 100)

I Any voter can become a candidate

I Voter’s place on the spectrum is fixed

I Voters will vote for the candidate who holds the closest views

I Win by random draw if candidates tieI Payoffs:

I Utility of 200 for winningI Cost of 100 to runI Cost of |x − y | for y winning (for x)

Page 2: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

Recall the Candidate-Voter Model:

I Have a political spectrum (0− 100)

I Any voter can become a candidate

I Voter’s place on the spectrum is fixed

I Voters will vote for the candidate who holds the closest views

I Win by random draw if candidates tieI Payoffs:

I Utility of 200 for winningI Cost of 100 to runI Cost of |x − y | for y winning (for x)

Page 3: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

Recall the Candidate-Voter Model:

I Have a political spectrum (0− 100)

I Any voter can become a candidate

I Voter’s place on the spectrum is fixed

I Voters will vote for the candidate who holds the closest views

I Win by random draw if candidates tieI Payoffs:

I Utility of 200 for winningI Cost of 100 to runI Cost of |x − y | for y winning (for x)

Page 4: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

Recall the Candidate-Voter Model:

I Have a political spectrum (0− 100)

I Any voter can become a candidate

I Voter’s place on the spectrum is fixed

I Voters will vote for the candidate who holds the closest views

I Win by random draw if candidates tieI Payoffs:

I Utility of 200 for winningI Cost of 100 to runI Cost of |x − y | for y winning (for x)

Page 5: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

Recall the Candidate-Voter Model:

I Have a political spectrum (0− 100)

I Any voter can become a candidate

I Voter’s place on the spectrum is fixed

I Voters will vote for the candidate who holds the closest views

I Win by random draw if candidates tie

I Payoffs:

I Utility of 200 for winningI Cost of 100 to runI Cost of |x − y | for y winning (for x)

Page 6: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

Recall the Candidate-Voter Model:

I Have a political spectrum (0− 100)

I Any voter can become a candidate

I Voter’s place on the spectrum is fixed

I Voters will vote for the candidate who holds the closest views

I Win by random draw if candidates tieI Payoffs:

I Utility of 200 for winningI Cost of 100 to runI Cost of |x − y | for y winning (for x)

Page 7: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I If 50 is the only person running, is this a Nash equilibrium?

I If 49 and 51 choose to run, 50 will loseIs this a problem?

I No. Nash equilibria only considers if one player changes theirstrategy

I If 30 and 70 run, is this a Nash equilibrium?

I Yes

I If 10 and 90 run, is this a Nash equilibrium?

I No

I So a Nash equilibrium occurs when:

I All candidates who run tieI No one can opt to run and tie or win

Page 8: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I If 50 is the only person running, is this a Nash equilibrium?I If 49 and 51 choose to run, 50 will lose

Is this a problem?

I No. Nash equilibria only considers if one player changes theirstrategy

I If 30 and 70 run, is this a Nash equilibrium?

I Yes

I If 10 and 90 run, is this a Nash equilibrium?

I No

I So a Nash equilibrium occurs when:

I All candidates who run tieI No one can opt to run and tie or win

Page 9: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I If 50 is the only person running, is this a Nash equilibrium?I If 49 and 51 choose to run, 50 will lose

Is this a problem?I No. Nash equilibria only considers if one player changes their

strategy

I If 30 and 70 run, is this a Nash equilibrium?

I Yes

I If 10 and 90 run, is this a Nash equilibrium?

I No

I So a Nash equilibrium occurs when:

I All candidates who run tieI No one can opt to run and tie or win

Page 10: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I If 50 is the only person running, is this a Nash equilibrium?I If 49 and 51 choose to run, 50 will lose

Is this a problem?I No. Nash equilibria only considers if one player changes their

strategy

I If 30 and 70 run, is this a Nash equilibrium?

I Yes

I If 10 and 90 run, is this a Nash equilibrium?

I No

I So a Nash equilibrium occurs when:

I All candidates who run tieI No one can opt to run and tie or win

Page 11: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I If 50 is the only person running, is this a Nash equilibrium?I If 49 and 51 choose to run, 50 will lose

Is this a problem?I No. Nash equilibria only considers if one player changes their

strategy

I If 30 and 70 run, is this a Nash equilibrium?I Yes

I If 10 and 90 run, is this a Nash equilibrium?

I No

I So a Nash equilibrium occurs when:

I All candidates who run tieI No one can opt to run and tie or win

Page 12: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I If 50 is the only person running, is this a Nash equilibrium?I If 49 and 51 choose to run, 50 will lose

Is this a problem?I No. Nash equilibria only considers if one player changes their

strategy

I If 30 and 70 run, is this a Nash equilibrium?I Yes

I If 10 and 90 run, is this a Nash equilibrium?

I No

I So a Nash equilibrium occurs when:

I All candidates who run tieI No one can opt to run and tie or win

Page 13: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I If 50 is the only person running, is this a Nash equilibrium?I If 49 and 51 choose to run, 50 will lose

Is this a problem?I No. Nash equilibria only considers if one player changes their

strategy

I If 30 and 70 run, is this a Nash equilibrium?I Yes

I If 10 and 90 run, is this a Nash equilibrium?I No

I So a Nash equilibrium occurs when:

I All candidates who run tieI No one can opt to run and tie or win

Page 14: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I If 50 is the only person running, is this a Nash equilibrium?I If 49 and 51 choose to run, 50 will lose

Is this a problem?I No. Nash equilibria only considers if one player changes their

strategy

I If 30 and 70 run, is this a Nash equilibrium?I Yes

I If 10 and 90 run, is this a Nash equilibrium?I No

I So a Nash equilibrium occurs when:

I All candidates who run tieI No one can opt to run and tie or win

Page 15: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I If 50 is the only person running, is this a Nash equilibrium?I If 49 and 51 choose to run, 50 will lose

Is this a problem?I No. Nash equilibria only considers if one player changes their

strategy

I If 30 and 70 run, is this a Nash equilibrium?I Yes

I If 10 and 90 run, is this a Nash equilibrium?I No

I So a Nash equilibrium occurs when:I All candidates who run tie

I No one can opt to run and tie or win

Page 16: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I If 50 is the only person running, is this a Nash equilibrium?I If 49 and 51 choose to run, 50 will lose

Is this a problem?I No. Nash equilibria only considers if one player changes their

strategy

I If 30 and 70 run, is this a Nash equilibrium?I Yes

I If 10 and 90 run, is this a Nash equilibrium?I No

I So a Nash equilibrium occurs when:I All candidates who run tieI No one can opt to run and tie or win

Page 17: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I Properties of this model:

I There are many Nash equilibriaI Not all equilibria have candidates crowded at the medianI If candidates become too extreme, more central candidates will

jump inI If you enter on the left, you make it more likely that someone

on the right wins (splitting the vote)

I Problems?

I Everyone decides whether or not to run at onceI Not everyone can practically runI Still assumes that politics lie on a single spectrum

Page 18: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I Properties of this model:I There are many Nash equilibria

I Not all equilibria have candidates crowded at the medianI If candidates become too extreme, more central candidates will

jump inI If you enter on the left, you make it more likely that someone

on the right wins (splitting the vote)

I Problems?

I Everyone decides whether or not to run at onceI Not everyone can practically runI Still assumes that politics lie on a single spectrum

Page 19: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I Properties of this model:I There are many Nash equilibriaI Not all equilibria have candidates crowded at the median

I If candidates become too extreme, more central candidates willjump in

I If you enter on the left, you make it more likely that someoneon the right wins (splitting the vote)

I Problems?

I Everyone decides whether or not to run at onceI Not everyone can practically runI Still assumes that politics lie on a single spectrum

Page 20: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I Properties of this model:I There are many Nash equilibriaI Not all equilibria have candidates crowded at the medianI If candidates become too extreme, more central candidates will

jump in

I If you enter on the left, you make it more likely that someoneon the right wins (splitting the vote)

I Problems?

I Everyone decides whether or not to run at onceI Not everyone can practically runI Still assumes that politics lie on a single spectrum

Page 21: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I Properties of this model:I There are many Nash equilibriaI Not all equilibria have candidates crowded at the medianI If candidates become too extreme, more central candidates will

jump inI If you enter on the left, you make it more likely that someone

on the right wins (splitting the vote)

I Problems?

I Everyone decides whether or not to run at onceI Not everyone can practically runI Still assumes that politics lie on a single spectrum

Page 22: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I Properties of this model:I There are many Nash equilibriaI Not all equilibria have candidates crowded at the medianI If candidates become too extreme, more central candidates will

jump inI If you enter on the left, you make it more likely that someone

on the right wins (splitting the vote)

I Problems?

I Everyone decides whether or not to run at onceI Not everyone can practically runI Still assumes that politics lie on a single spectrum

Page 23: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I Properties of this model:I There are many Nash equilibriaI Not all equilibria have candidates crowded at the medianI If candidates become too extreme, more central candidates will

jump inI If you enter on the left, you make it more likely that someone

on the right wins (splitting the vote)

I Problems?I Everyone decides whether or not to run at once

I Not everyone can practically runI Still assumes that politics lie on a single spectrum

Page 24: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I Properties of this model:I There are many Nash equilibriaI Not all equilibria have candidates crowded at the medianI If candidates become too extreme, more central candidates will

jump inI If you enter on the left, you make it more likely that someone

on the right wins (splitting the vote)

I Problems?I Everyone decides whether or not to run at onceI Not everyone can practically run

I Still assumes that politics lie on a single spectrum

Page 25: Math 180 - Game Theory - Penn Math

The Candidate-Voter Model

I Properties of this model:I There are many Nash equilibriaI Not all equilibria have candidates crowded at the medianI If candidates become too extreme, more central candidates will

jump inI If you enter on the left, you make it more likely that someone

on the right wins (splitting the vote)

I Problems?I Everyone decides whether or not to run at onceI Not everyone can practically runI Still assumes that politics lie on a single spectrum

Page 26: Math 180 - Game Theory - Penn Math

Another Game:

I Consider the following outcome matrix:

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What’s the name of this game?

I Rock Paper Scissors

I Are there any Nash equilibria?

I No

I What is the best strategy?

I Should be to pick each of rock,paper, and scissors randomlywith probability of 1

3 (Denote this as ( 13 ,

13 ,

13 ))

I This is an example of a mixed strategy

Page 27: Math 180 - Game Theory - Penn Math

Another Game:

I Consider the following outcome matrix:

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What’s the name of this game?

I Rock Paper Scissors

I Are there any Nash equilibria?

I No

I What is the best strategy?

I Should be to pick each of rock,paper, and scissors randomlywith probability of 1

3 (Denote this as ( 13 ,

13 ,

13 ))

I This is an example of a mixed strategy

Page 28: Math 180 - Game Theory - Penn Math

Another Game:

I Consider the following outcome matrix:

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What’s the name of this game?I Rock Paper Scissors

I Are there any Nash equilibria?

I No

I What is the best strategy?

I Should be to pick each of rock,paper, and scissors randomlywith probability of 1

3 (Denote this as ( 13 ,

13 ,

13 ))

I This is an example of a mixed strategy

Page 29: Math 180 - Game Theory - Penn Math

Another Game:

I Consider the following outcome matrix:

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What’s the name of this game?I Rock Paper Scissors

I Are there any Nash equilibria?

I No

I What is the best strategy?

I Should be to pick each of rock,paper, and scissors randomlywith probability of 1

3 (Denote this as ( 13 ,

13 ,

13 ))

I This is an example of a mixed strategy

Page 30: Math 180 - Game Theory - Penn Math

Another Game:

I Consider the following outcome matrix:

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What’s the name of this game?I Rock Paper Scissors

I Are there any Nash equilibria?I No

I What is the best strategy?

I Should be to pick each of rock,paper, and scissors randomlywith probability of 1

3 (Denote this as ( 13 ,

13 ,

13 ))

I This is an example of a mixed strategy

Page 31: Math 180 - Game Theory - Penn Math

Another Game:

I Consider the following outcome matrix:

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What’s the name of this game?I Rock Paper Scissors

I Are there any Nash equilibria?I No

I What is the best strategy?

I Should be to pick each of rock,paper, and scissors randomlywith probability of 1

3 (Denote this as ( 13 ,

13 ,

13 ))

I This is an example of a mixed strategy

Page 32: Math 180 - Game Theory - Penn Math

Another Game:

I Consider the following outcome matrix:

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What’s the name of this game?I Rock Paper Scissors

I Are there any Nash equilibria?I No

I What is the best strategy?I Should be to pick each of rock,paper, and scissors randomly

with probability of 13 (Denote this as ( 1

3 ,13 ,

13 ))

I This is an example of a mixed strategy

Page 33: Math 180 - Game Theory - Penn Math

Another Game:

I Consider the following outcome matrix:

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What’s the name of this game?I Rock Paper Scissors

I Are there any Nash equilibria?I No

I What is the best strategy?I Should be to pick each of rock,paper, and scissors randomly

with probability of 13 (Denote this as ( 1

3 ,13 ,

13 ))

I This is an example of a mixed strategy

Page 34: Math 180 - Game Theory - Penn Math

Expected Payout

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What is the expected payout of (13 ,13 ,

13) against (1, 0, 0)?(

u((13 ,13 ,

13), (1, 0, 0))

)

I 0

I Note that the expected payout is weighted average of thepayouts of the pure strategies (with positive probabilities)

Page 35: Math 180 - Game Theory - Penn Math

Expected Payout

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What is the expected payout of (13 ,13 ,

13) against (1, 0, 0)?(

u((13 ,13 ,

13), (1, 0, 0))

)I 0

I Note that the expected payout is weighted average of thepayouts of the pure strategies (with positive probabilities)

Page 36: Math 180 - Game Theory - Penn Math

Expected Payout

0, 0

1, -1

-1, 1

0, 0

1, -1

-1, 1

-1, 1 1, -1 0, 0R P S

R

P

S

I What is the expected payout of (13 ,13 ,

13) against (1, 0, 0)?(

u((13 ,13 ,

13), (1, 0, 0))

)I 0

I Note that the expected payout is weighted average of thepayouts of the pure strategies (with positive probabilities)

Page 37: Math 180 - Game Theory - Penn Math

Weighted Averages

I How can you raise the average batting average of a baseballteam?

I By cutting people with a low batting averageI If the average batting average is maximized, all players must

have the same batting average

I If pi is a best response to the other strategies, all the purestrategies used in pi are best responses to p−i

I Consider this modified Battle of the Sexes game:

C DC

D

3, 2

0, 0 2, 3

1, 1You

Date

I Is ( 12 ,

12 ) a best response to (0, 1)?

I No - you should drop C

Page 38: Math 180 - Game Theory - Penn Math

Weighted Averages

I How can you raise the average batting average of a baseballteam?

I By cutting people with a low batting average

I If the average batting average is maximized, all players musthave the same batting average

I If pi is a best response to the other strategies, all the purestrategies used in pi are best responses to p−i

I Consider this modified Battle of the Sexes game:

C DC

D

3, 2

0, 0 2, 3

1, 1You

Date

I Is ( 12 ,

12 ) a best response to (0, 1)?

I No - you should drop C

Page 39: Math 180 - Game Theory - Penn Math

Weighted Averages

I How can you raise the average batting average of a baseballteam?

I By cutting people with a low batting averageI If the average batting average is maximized, all players must

have the same batting average

I If pi is a best response to the other strategies, all the purestrategies used in pi are best responses to p−i

I Consider this modified Battle of the Sexes game:

C DC

D

3, 2

0, 0 2, 3

1, 1You

Date

I Is ( 12 ,

12 ) a best response to (0, 1)?

I No - you should drop C

Page 40: Math 180 - Game Theory - Penn Math

Weighted Averages

I How can you raise the average batting average of a baseballteam?

I By cutting people with a low batting averageI If the average batting average is maximized, all players must

have the same batting average

I If pi is a best response to the other strategies, all the purestrategies used in pi are best responses to p−i

I Consider this modified Battle of the Sexes game:

C DC

D

3, 2

0, 0 2, 3

1, 1You

Date

I Is ( 12 ,

12 ) a best response to (0, 1)?

I No - you should drop C

Page 41: Math 180 - Game Theory - Penn Math

Weighted Averages

I How can you raise the average batting average of a baseballteam?

I By cutting people with a low batting averageI If the average batting average is maximized, all players must

have the same batting average

I If pi is a best response to the other strategies, all the purestrategies used in pi are best responses to p−i

I Consider this modified Battle of the Sexes game:

C DC

D

3, 2

0, 0 2, 3

1, 1You

Date

I Is ( 12 ,

12 ) a best response to (0, 1)?

I No - you should drop C

Page 42: Math 180 - Game Theory - Penn Math

Weighted Averages

I How can you raise the average batting average of a baseballteam?

I By cutting people with a low batting averageI If the average batting average is maximized, all players must

have the same batting average

I If pi is a best response to the other strategies, all the purestrategies used in pi are best responses to p−i

I Consider this modified Battle of the Sexes game:

C DC

D

3, 2

0, 0 2, 3

1, 1You

Date

I Is ( 12 ,

12 ) a best response to (0, 1)?

I No - you should drop C

Page 43: Math 180 - Game Theory - Penn Math

Nash Equilibrium

I Mixed strategies (p1, . . . , pn) are a Nash equilibrium if pi is abest response to p−i

I Each player asks “if the other players stuck with theirstrategies, am I better off mixing the ratio of strategies?”

I If pi is a best response to p−i , the payouts of the purestrategies in pi are equal

I Note that pure Nash equilibria are still Nash equilibria

Page 44: Math 180 - Game Theory - Penn Math

Nash Equilibrium

I Mixed strategies (p1, . . . , pn) are a Nash equilibrium if pi is abest response to p−i

I Each player asks “if the other players stuck with theirstrategies, am I better off mixing the ratio of strategies?”

I If pi is a best response to p−i , the payouts of the purestrategies in pi are equal

I Note that pure Nash equilibria are still Nash equilibria

Page 45: Math 180 - Game Theory - Penn Math

Nash Equilibrium

I Mixed strategies (p1, . . . , pn) are a Nash equilibrium if pi is abest response to p−i

I Each player asks “if the other players stuck with theirstrategies, am I better off mixing the ratio of strategies?”

I If pi is a best response to p−i , the payouts of the purestrategies in pi are equal

I Note that pure Nash equilibria are still Nash equilibria

Page 46: Math 180 - Game Theory - Penn Math

Nash Equilibrium

I Mixed strategies (p1, . . . , pn) are a Nash equilibrium if pi is abest response to p−i

I Each player asks “if the other players stuck with theirstrategies, am I better off mixing the ratio of strategies?”

I If pi is a best response to p−i , the payouts of the purestrategies in pi are equal

I Note that pure Nash equilibria are still Nash equilibria