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An Introduction to... Evolutionary Game Theory By Jin Xiao, Jeff Thomas, Jeff Westwell

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Page 1: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

An Introduction to...

Evolutionary GameTheory

By Jin Xiao,Jeff Thomas,Jeff Westwell

Page 2: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

How would game theory view this?

Page 3: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

What will we discuss?

• Brief History of Game Theory

• Payoff Matrix

• Types of Games

• Basic Strategies

• Evolutionary Concepts

• Limitations and Problems

Page 4: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Brief History of Game Theory• 1913 - E. Zermelo provided the first theorem of game theory

asserts that chess is strictly determined

• 1928 - John von Neumann proved the minimax theorem

• 1944 - John von Neumann / Oskar Morgenstern’s wrote

"Theory of Games and Economic Behavior”

• 1950-1953, John Nash describes Nash equilibrium

• 1972 - John Maynard Smith wrote

“Game Theory and The Evolution of Fighting”

Page 5: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

RationalityAssumptions:

• humans are rational beings

• humans always seek the best alternative in aset of possible choices

Why assume rationality?

• narrow down the range of possibilities

• predictability

Page 6: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Utility Theory

Utility Theory based on:

• rationality

• maximization of utility

It is a quantification of a person's preferenceswith respect to certain objects.

Page 7: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

What is Game Theory?

Game theory is a study of how tomathematically determine the best strategyfor given conditions in order to optimizethe outcome

Page 8: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Game Theory

• Finding acceptable, if not optimal, strategiesin conflict situations.

• Abstraction of real complex situation

• Game theory is highly mathematical

• Game theory assumes all humaninteractions can be understood andnavigated by presumptions.

Page 9: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Why is game theoryimportant?

• All intelligent beings make decisions all thetime.

• AI needs to perform these tasks as a result.

• Helps us to analyze situations morerationally and formulate an acceptablealternative with respect to circumstance.

Page 10: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

The Payoff Matrix

Player#1

Player #2

Strategy #1 Strategy #2

Strategy #1

Strategy #2

Payoff (1,1) Payoff (1,2)

Payoff (2,1) Payoff (2,2)

Page 11: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Types of Games

• Sequential vs. Simultaneous moves

• Single Play vs. Iterated

• Zero vs. non-zero sum

• Perfect vs. Imperfect information

• Cooperative vs. conflict

Page 12: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Zero-Sum Games

• The sum of the payoffs remains constantduring the course of the game.

• Two sides in conflict

• Being well informed always helps a player

Page 13: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Non-zero Sum Game

• The sum of payoffs is not constant duringthe course of game play.

• Players may co-operate or compete

• Being well informed may harm a player.

Page 14: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Games of Perfect Information

• The information concerning an opponent’smove is well known in advance.

• All sequential move games are of this type.

Page 15: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Imperfect Information

• Partial or no information concerning theopponent is given in advance to the player’sdecision.

• Imperfect information may be diminishedover time if the same game with the sameopponent is to be repeated.

Page 16: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Key Area of Interest

• chance

• strategy

Page 17: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Prisoner’s Dilemma

Page 18: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Prisoner’s Dilemma

Page 19: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Games of Conflict

• Two sides competing against each other

• Usually caused by complete lack ofinformation about the opponent or the game

• Characteristic of zero-sum games

Page 20: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Games of Co-operation

Players may improve payoff through

• communicating

• forming binding coalitions & agreements

• do not apply to zero-sum games

Prisoner’s Dilemma

with Cooperation

Page 21: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Prisoner’s Dilemma with Iteration

• Infinite number of iterations

– Fear of retaliation

• Fixed number of iteration

– Domino effect

Page 22: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Basic Strategies

1. Plan ahead and look back

2. Use a dominating strategy if possible

3. Eliminate any dominated strategies

4. Look for any equilibrium

5. Mix up the strategies

Page 23: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Plan ahead and look back

Page 24: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

If you have a Dominatingstrategy, use it

Usestrategy 1

Page 25: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Eliminate any Dominatedstrategy

Eliminatestrategy 2 asit’s dominatedby strategy 1

Page 26: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Look for any equilibrium

• Dominating Equilibrium

• Minimax Equilibrium

• Nash Equilibrium

Page 27: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Maximin & MinimaxEquilibrium

• Minimax - to minimize the maximum loss(defensive)

• Maximin - to maximize the minimum gain(offensive)

• Minimax = Maximin

Page 28: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Maximin & MinimaxEquilibrium Strategies

Page 29: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Definition: Nash Equilibrium

“If there is a set of strategies with the propertythat no player can benefit by changing herstrategy while the other players keep theirstrategies unchanged, then that set ofstrategies and the corresponding payoffsconstitute the Nash Equilibrium. “

Source: http://www.lebow.drexel.edu/economics/mccain/game/game.html

Page 30: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Is this a Nash Equilibrium?

Page 31: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Cost to pressbutton = 2 units

When button is pressed,food given = 10 units

Boxed Pigs Example

Page 32: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Decisions, decisions...

Page 33: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Mixed Strategy

Page 34: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Mixed Strategy Solution

Value in Safe

Probability of being Guarded

Expected Loss

Safe 1 10,000$ 1 / 11 9,091$ Safe 2 100,000$ 10 / 11 9,091$ Both 110,000$

Page 35: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Evolutionary Game Theory

• Natural selection replaces rational behavior

• Survival of the fittest

• Why use evolution to determine a strategy?

Page 36: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Hawk / Dove Game

Page 37: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Evolutionary Stable Strategy

• Introduced by Maynard Smith and Price(1973)

• Strategy becomes stable throughout thepopulation

• Mutations becoming ineffective

Page 38: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the
Page 39: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

ESS of Hawk/Dove Game

-6

-4

-2

0

2

4

6

8

10

12

0 20 40 60 80 100

% of Population with Dove Strategy

Exp

ecte

d P

ayo

ff

Hawk Strategy Dove Strategy

Page 40: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the
Page 41: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

ESS of Hawk/Dove Game

-6

-4

-2

0

2

4

6

8

10

12

0 20 40 60 80 100

% of Population with Dove Strategy

Exp

ecte

d P

ayo

ff

Hawk Strategy Dove Strategy

Page 42: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Where is game theory currently used?

– Ecology

– Networks

– Economics

Page 43: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Limitations & Problems

• Assumes players always maximize theiroutcomes

• Some outcomes are difficult to provide autility for

• Not all of the payoffs can be quantified

• Not applicable to all problems

Page 44: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Indiana Jones Scenario

Page 45: An Introduction to Evolutionary Game Theorypages.cpsc.ucalgary.ca/~jacob/Courses/.../Slides/04.4.2-EvolGameTh… · Brief History of Game Theory • 1913 - E. Zermelo provided the

Summary• What is game theory?

– Abstraction modeling multi-person interactions

• How is game theory applied?

– Payoff matrix contains each person’s utilities forvarious strategies

• Who uses game theory?

– Economists, Ecologists, Network people,...

• How is this related to AI?

– Provides a method to simulate a thinking agent