why how we learn matters

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Why How We Learn Matters Russell Golman Scott E Page

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Why How We Learn Matters. Russell Golman Scott E Page. Overview. BIG Picture Game Theory Basics Nash Equilibrium Equilibrium something about the other. Stability Basins Learning Rules Why Learning Matters. Big Question. - PowerPoint PPT Presentation

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Page 1: Why How We Learn Matters

Why How We Learn Matters

Russell Golman

Scott E Page

Page 2: Why How We Learn Matters

Overview

• BIG Picture• Game Theory Basics• Nash Equilibrium

– Equilibrium something about the other. – Stability– Basins

• Learning Rules• Why Learning Matters

Page 3: Why How We Learn Matters

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Page 4: Why How We Learn Matters

Big Question

If you had one word to describe the social, political, and economic worlds around you would you choose equilibrium or complex?

Page 5: Why How We Learn Matters

Methodological Question

Do we construct simple, illustrative, insight generating models (PD, Sandpile, El Farol) or do we construct high fidelity, realistic models?

Page 6: Why How We Learn Matters

My Answer: BOTH!

Both types of models are useful in their own right. In addition, each tells us something about the other.

Page 7: Why How We Learn Matters

My Answer: BOTH!

Knowledge of simple models helps us construct better high fidelity models.

Large models show if insights from simple models still apply.

Page 8: Why How We Learn Matters

Today’s Exercise

How does how agents learn influence outcomes?

Page 9: Why How We Learn Matters

Step Way Back

Complex Adaptive System

- Agents

- Variation

- Selection*

Page 10: Why How We Learn Matters

Examples

Best respond to current state

Better respond

Mimic best

Mimic better

Include portions of best or better

Random with death of the unfit

Page 11: Why How We Learn Matters

Equilibrium Science

We can start by looking at the role that learning rules play in equilibrium systems. This will give us some insight into whether they’ll matter in complex systems.

Page 12: Why How We Learn Matters

Game Theory

• Players• Actions• Payoffs

Page 13: Why How We Learn Matters

Players

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Page 14: Why How We Learn Matters

Actions

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Cooperate: C Defect: D

Page 15: Why How We Learn Matters

Payoffs

4,4 0,6

6,0 2,2

C D

C

D

Page 16: Why How We Learn Matters

Best Responses

4,4 0,6

6,0 2,2

C D

C

D

Page 17: Why How We Learn Matters

Best Responses

4,4 0,6

6,0 2,2

C D

C

D

Page 18: Why How We Learn Matters

Nash Equilibrium

4,4 0,6

6,0 2,2

C D

C

D 2,2

Page 19: Why How We Learn Matters

“Equilibrium” Based Science

Step 1: Set up gameStep 2: Solve for equilibriumStep 3: Show how equilibrium depends

on parameters of modelStep 4: Provide empirical support

Page 20: Why How We Learn Matters

Is Equilibrium Enough?

Existence: Equilibrium exists

Stability: Equilibrium is stable

Attainable: Equilibrium is attained by a learning rule.

Page 21: Why How We Learn Matters

Stability

Stability can only be defined relative to a learning dynamic. In dynamical systems, we often take that dynamic to be a best response function, but with human actors we need not assume people best respond.

Page 22: Why How We Learn Matters

Existence Theorem

Theorem: Finite number of players, finite set of actions, then there exists a Nash Equilibrium.

Pf: Show best response functions are upper hemi continuous and then apply Kakutani’s fixed point theorem

Page 23: Why How We Learn Matters

Battle of Sexes Game

3,1 0,0

0,0 1,3

EF CG

EF

CG

Page 24: Why How We Learn Matters

Three Equilibria

3,1 0,0

0,0 1,3

1/4 3/4

3/4

1/4

Page 25: Why How We Learn Matters

Unstable Mixed?

3,1 0,0

0,0 1,3

1/4 +e 3/4 - e

EF

CG

3/4 + 3e

3/4 - 3e

Page 26: Why How We Learn Matters

Note the Implicit Assumption

Our stability analysis assumed that Player 1 would best respond to Player 2’s tremble. However, the learning rule could be go to the mixed strategy equilibrium. If so, Player 1 would sit tight and Player 2 would return to the mixed strategy equilibrium.

Page 27: Why How We Learn Matters

Empirical Foundations

We need to have some understanding of how people learn and adapt to say anything about stability.

Page 28: Why How We Learn Matters

Classes of Learning Rules

Belief Based Learning Rules: People best respond given their beliefs about how other people play.

Replicator Learning Rules: People replicate successful actions of others.

Page 29: Why How We Learn Matters

Examples

Belief Based Learning Rules:

Best response functions

Replicator Learning Rules:

Replicator dynamics

Page 30: Why How We Learn Matters

Stability Results

An extensive literature provides conditions (fairly week) under which the two learning rules have identical stability property.

Synopsis: Learning rules do not matter

Page 31: Why How We Learn Matters

Basins Question

Do games exist in which best response dynamics and replicator dynamics produce very different basins of attraction?

Question: Does learning matter?

Page 32: Why How We Learn Matters

Best Response Dynamics

x = mixed strategy of Player 1

y = mixed strategy of Player 2

dx/dt = BR(y) - x

dy/dt = BR(x) - y

Page 33: Why How We Learn Matters

Replicator Dynamics

dxi/dt = xi( i - ave)

dyi/dt = yi( i - ave)

Page 34: Why How We Learn Matters

Symmetric Matrix Game

60 60 30

30 70 20

70 25 35

A

B

C

A B C

Page 35: Why How We Learn Matters

Conceptualization

Imagine a large population of agents playing this game. Each chooses an action. The population distribution over actions creates a mixed strategy. We can then study the dynamics of that population given different learning rules.

Page 36: Why How We Learn Matters

Best Response Basins

60 60 30

30 70 20

70 25 35

A

B

C

A B C

A > B iff 60pA + 60pB + 30pC > 30pA + 70pB + 20pC

A > C iff 60pA + 60pB + 30pC > 70pA + 25pB + 35pC

Page 37: Why How We Learn Matters

Best Response Basins

A

A

B

C

C

BC B

Page 38: Why How We Learn Matters

Stable Equilibria

A

A

B

C

C

BC B

Page 39: Why How We Learn Matters

Best Response Basins

A

A

B

C

C

BA B

Page 40: Why How We Learn Matters

Replicator Dynamics

A

A

B

C

C

B? B

Page 41: Why How We Learn Matters

Replicator Dynamics Basins

A

A

B

C

C

BA BB

Page 42: Why How We Learn Matters

Recall: Basins Question

Do games exist in which best response dynamics and replicator dynamics produce very different basins of attraction?

Question: Does learning matter?

Page 43: Why How We Learn Matters

Conjecture

For any > 0, There exists a symmetric matrix game such that the basins of attraction for distinct equilibria under continuous time best response dynamics and replicator dynamics overlap by less than

Page 44: Why How We Learn Matters

Results

Thm 1 (SP): Can be done if number of actions goes to infinity

Page 45: Why How We Learn Matters

Results

Thm 1 (SP): Can be done if number of actions goes to infinity

Thm 2 (RG): Can be done if number of actions scales with 1/

Page 46: Why How We Learn Matters

Results

Thm 1 (SP): Can be done if number of actions goes to infinity

Thm 2 (RG): Can be done if number of actions scales with 1/

Thm 3 (RG): Cannot be done with two actions.

Page 47: Why How We Learn Matters

Results

Thm 1 (SP): Can be done if number of actions goes to infinity

Thm 2 (RG): Can be done if number of actions scales with 1/

Thm 3 (RG): Cannot be done with two actions.

Thm 4 (SP): Can be done with four!

Page 48: Why How We Learn Matters

Collective Action Game

SI Coop Pred Naive

2 2 2 2

1 N+1 1 1

0 0 0 N2

0 0 -N2 0

SI

Coop

Pred

Naive

Page 49: Why How We Learn Matters

Intuition: Naïve Goes Away

SI Coop

Pred

Page 50: Why How We Learn Matters

Intuition: Naïve Goes Away

SI Coop

Pred

Coop

SI

Page 51: Why How We Learn Matters

Best Response

SI Coop

Pred

Coop

SI

Page 52: Why How We Learn Matters

Best ResponsePred

Coop

SI

Page 53: Why How We Learn Matters

Replicator

SI Coop

Pred

Coop

SI

Page 54: Why How We Learn Matters

Collective Action Game

SI Coop Pred Naive

2 2 2 2

1 N+1 1 1

0 0 0 N2

0 0 -N2 0

SI

Coop

Pred

Naive

Page 55: Why How We Learn Matters

The Math

dxi/dt = xi( i - ave)

ave = 2xS + xC (1+NxC)

dxc/dt = xc[(1+ NxC- - 2xS - xC (1+NxC)]

dxc/dt = xc[(1+ NxC)(1- xC) - 2xS]

Page 56: Why How We Learn Matters

Choose N > 1/

Assume xc >

dxc/dt = xc[(1+ NxC)(1- xC) - 2xS]

dxc/dt > [2(1- ) - 2(1- )] = 0

Therefore, xc always increases.

Page 57: Why How We Learn Matters

Aside: Why Care?

Replicator dynamics often thought of as being cultural learning. Best response learning thought of as self interested learning. Societies differ by degree of individualism. These results show that how society is structure could affect the ability to solve collective action problems.

Page 58: Why How We Learn Matters

Results (Cont’d)

Conjecture (SP): There does not exist a game with three actions such that the basins have vanishing overlap.

Page 59: Why How We Learn Matters

Results (Cont’d)

Conjecture (SP): There does not exist a game with three actions such that the basins have vanishing overlap.

Thm 5 (RG): There does exist a game with three actions such that the basins have vanishing overlap

Page 60: Why How We Learn Matters

Genericity of Results

Example

Proof for a functional form

Proof for a class of functions

General Result

Page 61: Why How We Learn Matters

What do we have?

Examples: 3 and 4 dimensions

General Result: 3 dimensions is minimal.

Page 62: Why How We Learn Matters

Another General Result

Recall that in the (very cool) four dimensional example, that initially predatory behavior was a best response with probability one. Moreover, it was not an equilibrium.

Turns out, this is always true!!

Page 63: Why How We Learn Matters

Theorem: In any symmetric matrix game for which best response and replicator dynamics attain different equilibria with probability one, there exists an action A that is both an initial best response with probability one and is not an equilibrium.

Page 64: Why How We Learn Matters

From Science to Art

Insight: If I’m constructing a large scale ABM and some actions will win for a short time and then die off, then I had better experiment with lots of learning rules.

Page 65: Why How We Learn Matters

Two Aggregation Questions

Q1: What if I take an average of the learning rules?

Q2: What if some people use one rule and some use another? Do I get the same result as everyone used the same hybrid rule?

Page 66: Why How We Learn Matters

Two Aggregation Questions

Q1: What if I take an average of the learning rules? Anything you want

Q2: What if some people use one rule and some use another? Do I get the same result as everyone used the same hybrid rule? No

Page 67: Why How We Learn Matters

Why Complexity?

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Complex Issues

Global Inequality

Crime/Education

Health Care

Ecosystem Management

Global Climate Change

International Relations/Terrorism

Epidemics

Page 69: Why How We Learn Matters

Needs

More “thinking tools” PD, Sandpile, etc..

More science and improved art for constructing high fidelity models.