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A4M33MAS - Multiagent Systems Introduction to Game Theory Michal Pechoucek & Branislav Bosansky Department of Computer Science Czech Technical University in Prague In parts based on Kevin Leyton-Brown: Foundations of Multiagent Systems an introduction to algorithmic game theory, mechanism design and auctions
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Page 1: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

A4M33MAS - Multiagent Systems Introduction to Game Theory

Michal Pechoucek & Branislav BosanskyDepartment of Computer Science Czech Technical University in Prague

In parts based on Kevin Leyton-Brown: Foundations of Multiagent Systems an introduction to algorithmic game theory, mechanism design and auctions

Page 2: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Game Theory• Game theory is the study of strategic decision making, the study of

mathematical models of conflict and cooperation between intelligent rational decision-makers, interactive decision theory

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Game Theory• Game theory is the study of strategic decision making, the study of

mathematical models of conflict and cooperation between intelligent rational decision-makers, interactive decision theory – Given the rule of the game, game theory studies strategic behaviour

of the agents in the form of a strategy (e.g. optimality, stability) – Given the strategic behavior of the agents, mechanism design

(reverse game theory) studies/designs the rule of games with respect to a specific outcome of the game

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Page 4: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Game TheoryYoav Shoham, Kevin Leyton-Brown, Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations Cambridge University Press, 2009

http://www.masfoundations.org

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Types of Games• Cooperative or non-cooperative • Symmetric and asymmetric • Zero-sum and non-zero-sum • Simultaneous and sequential • Combinatorial games and imperfect information games • Infinitely long games • Discrete and continuous games, differential games

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TCP Backoff Game• Consider this situation as a two-player game:

– both use a correct implementation: both get 1 ms delay – one correct, one defective: 4 ms delay for correct, 0 ms for defective – both defective: both get a 3 ms delay.

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Page 7: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

TCP Backoff Game

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• Consider this situation as a two-player game: – both use a correct implementation: both get 1 ms delay – one correct, one defective: 4 ms delay for correct, 0 ms for defective – both defective: both get a 3 ms delay.

• Questions: – What action should a player of the game take? – Would all users behave the same in this scenario? – What global patterns of behaviour should the system designer expect? – Under what changes to the delay numbers would behavior be the same? – What effect would communication have? – Repetitions? (finite? infinite?) – Does it matter if I believe that my opponent is rational?

Page 8: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Game definition

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Game definition

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C D

Cx ⎯1, ⎯1 ⎯ 4, 0

Dx 0, ⎯ 4 ⎯3, ⎯3

Page 10: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Other Games: Coordination Games

driving side

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Left Right

Leftx 1 0

Rightx 0 1

Page 11: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Other Games: Coordination Games

driving side battle of sexes

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Left Right

Leftx 1 0

Rightx 0 1

Ball Football

Ballx 2, 1 0, 0

Footballx 0, 0 1, 2

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Other Games: Prisoners Dilemma

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BC BD

AC 1 ,1 5, 0

AD 0, 5 3, 3

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a, a b, c

c, b d, d

c ⌫ a ⌫ d ⌫ b

Other Games: Prisoners Dilemma

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BC BD

AC

AD

any game where

Page 14: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Other Games: Matching Pennies

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Heads Tails

Headsx 1, -1 -1, 1

Tailsx -1, 1 1, -1

Heads Tails

Headsx 1 -1

Tailsx -1 1

Page 15: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Other Games: Rock-paper-scissors

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Rock Paper Scissors

Rockx 0 -1 1

Paperx 1 0 -1

Scissorsx -1 1 0

Page 16: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

strategy refers to a decision (about action choice) at each stage of the game that the agent makes and which leads to an outcome outcome is the set of possible states resulting from agent’s decision making strategy profile refers to the set of strategies played by the agents. Set of strategy profiles:

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Properties of the games

Page 17: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Properties of the games• Social welfare (collective utility):

• Cooperative agents choose such that maximizes • Self-interested (individually rational) agents choose such that

maximizes

• When designing a multiagent system designers worry about: – individual rationality of each agent – social welfare and welfare efficiency – stability of the strategy (action) profile

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U(a) =X

8iui(ai)

Page 18: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Solution Concepts• Pareto Efficiency • Social welfare optimality • Nash equilibrium • Maxmin • Dominant strategies • Correlated equilibrium • Minimax regret • Stackelberg equilibrium • Perfect equilibrium • - Nash equilibrium

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Solution Concepts• Pareto Efficiency • Social welfare optimality • Nash equilibrium • Maxmin • Dominant strategies • Correlated equilibrium • Minimax regret • Stackelberg equilibrium • Perfect equilibrium • - Nash equilibrium

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Page 20: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Solution Concepts• Pareto Efficiency • Social welfare optimality • Nash equilibrium • Maxmin • Dominant strategies • Correlated equilibrium • Minimax regret • Stackelberg equilibrium • Perfect equilibrium • - Nash equilibrium

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Pareto Efficiency• Pareto Efficiency:

– action (strategy) profile is Pareto optimal if there is no other action that at least one agent is better off and no other agent is worse off than in the given profile

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Pareto Efficiency• Pareto Efficiency:

– action (strategy) profile is Pareto optimal if there is no other action that at least one agent is better off and no other agent is worse off than in the given profile

• Dominance: – measure comparing two strategies. b dominates weakly a as follows:

– dominant strategy: strategy that is not dominated by any other strategy

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• Pareto Efficiency: – action (strategy) profile is Pareto optimal if there is no other action

that at least one agent is better off and no other agent is worse off than in the given profile

• Dominance: – measure comparing two strategies. b dominates weakly a as follows:

– dominant strategy: strategy that is not dominated by any other strategy

Pareto efficient strategy is such a strategy that is not weakly dominated by any other strategy

Pareto Efficiency

2323

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Pareto Efficiency

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C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Pareto Efficiency

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C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Pareto Efficiency

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Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

Page 27: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Pareto Efficiency

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Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

Page 28: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Pareto Efficiency

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Left Right

Leftx 1 0

Rightx 0 1

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

Page 29: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Pareto Efficiency

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Left Right

Leftx 1 0

Rightx 0 1

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Pareto Efficiency

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Left Right

Leftx 1 0

Rightx 0 1

B F

Bx 2, 1 0, 0

Fx 0, 0 1, 2

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

Left Right

Leftx 1 0

Rightx 0 1

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

Page 31: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Pareto Efficiency

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Left Right

Leftx 1 0

Rightx 0 1

B F

Bx 2, 1 0, 0

Fx 0, 0 1, 2

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

Left Right

Leftx 1 0

Rightx 0 1

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

Page 32: A4M33MAS - Multiagent Systems Introduction to Game Theorycw.fel.cvut.cz/wiki/_media/courses/be4m36mas/mas2016-l03-gt-intr… · Introduction to Game Theory Michal Pechoucek & Branislav

Solution Concepts• Pareto Efficiency • Social welfare optimality • Nash equilibrium • Maxmin • Dominant strategies • Correlated equilibrium • Minimax regret • Stackelberg equilibrium • Perfect equilibrium • - Nash equilibrium

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Nash Equilibrium

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• If you know what everyone else was going to do, it would be easy to pick your own actions

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Nash Equilibrium

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8i, ai 2 BR(a�i)

Definition (Nash Equilibrium) The strategy profile is in Nash Equilibrium iffa = ha1, . . . , ani

Definition (Best Response) a⇤i 2 BR(a�i) i↵ 8ai 2 Ai, ui(a

⇤i , a�i) � ui(ai, a�i)

• If you know what everyone else was going to do, it would be easy to pick your own actions

• Let now ai = ha1, . . . , ai�1, ai+1, . . . , ani. a = (a�i, ai)

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Nash Equilibrium

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• Nash equilibrium, is a set of strategies, one for each player, such that no player has incentive to unilaterally change her action. Players are in equilibrium if a change in strategies by any one of them would lead that player to earn less than if she remained with her current strategy.

• Strong Nash Equilibrium is such an equilibrium that is stable against deviations by cooperation.

8i, ai 2 BR(a�i)

Definition (Nash Equilibrium) The strategy profile is in Nash Equilibrium iffa = ha1, . . . , ani

Definition (Best Response) a⇤i 2 BR(a�i) i↵ 8ai 2 Ai, ui(a

⇤i , a�i) � ui(ai, a�i)

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Nash Equilibrium

36

Definition (Weak Nash Equilibrium) The strategy profile is in Weak NE iff it is not Strict NE

8i, ai 2 BR(a�i)

a = ha1, . . . , ani|BR(a�i)| = 1

Definition (Strict Nash Equilibrium) The strategy profile is in Strict Nash iff where

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• Nash equilibrium, is a set of strategies, one for each player, such that no player has incentive to unilaterally change her action. Players are in equilibrium if a change in strategies by any one of them would lead that player to earn less than if she remained with her current strategy.

• Strong Nash Equilibrium is such an equilibrium that is stable against deviations by cooperation.

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Nash Equilibrium

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C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Nash Equilibrium

38

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Nash Equilibrium

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Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Nash Equilibrium

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Left Right

Leftx 1 0

Rightx 0 1

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Nash Equilibrium

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Left Right

Leftx 1 0

Rightx 0 1

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Nash Equilibrium

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Left Right

Leftx 1 0

Rightx 0 1

B F

Bx 2, 1 0, 0

Fx 0, 0 1, 2

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Nash Equilibrium

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Left Right

Leftx 1 0

Rightx 0 1

B F

Bx 2, 1 0, 0

Fx 0, 0 1, 2

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Strong Nash Equilibrium

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Left Right

Leftx 1 0

Rightx 0 1

B F

Bx 2, 1 0, 0

Fx 0, 0 1, 2

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Strong Nash Equilibrium

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Left Right

Leftx 1 0

Rightx 0 1

B F

Bx 2, 1 0, 0

Fx 0, 0 1, 2

Heads Tails

Headsx 1 -1

Tailsx -1 1

C D

C -1, -1 -4, 0

D 0, -4 -3, -3

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Prisoners Dilemma: PE, NE

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BC BD

AC 1, 1 5, 0

AD 0, 5 3, 3

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Prisoners Dilemma: PE, NE

47

BC BD

AC 1, 1 5, 0

AD 0, 5 3, 3

PE

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Prisoners Dilemma: PE, NE

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BC BD

AC 1, 1 5, 0

AD 0, 5 3, 3

PE NE

The paradox of Prisoner’s Dilemma: the Nash equilibrium is the only non-Pareto-optimal outcome

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Prisoners Dilemma: PE, NE

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BC BD

AC 1, 1 5, 0

AD 0, 5 3, 3

PENE

dominant

The paradox of Prisoner’s Dilemma: the Nash equilibrium is the only non-Pareto-optimal outcome

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Prisoners Dilemma: PE, NE

50

BC BD

AC 1, 1 5, 0

AD 0, 5 3, 3

PE

NEdominant

social welfare optimal

The paradox of Prisoner’s Dilemma: the Nash equilibrium is the only non-Pareto-optimal outcome

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Example: Routing

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• 1,000 drivers travel from S to D on either S→A→D or S→B→D • Road from S → A, B → D is long: t = 50 minutes for any |cars| • Road from A → D, S → B is shorter but is narrow t = |cars|/25

• Nash equilibrium: – 500 cars go through A, 500 through B with time is 50 + 500/25 = 70m – If a single driver changes the route, there are 501 cars on that route: time ↑

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Braess’s Paradox• Suppose we add a new road from B to A • The road is so wide and short that it takes 0 minutes to traverse it • Nash equilibrium:

– All 1000 cars go S→B→A→D – Time for S→B is 1000/25 = 40 minutes – Total time is 80 minutes

• To see that this is an equilibrium: – If driver goes S→A→D, his/her cost is 50 + 40 = 90 minutes – If driver goes S→B→D, his/her cost is 40 + 50 = 90 minutes – Both are dominated by S→B→A→D

• To see that it’s the only Nash equilibrium: – For every traffic pattern, S→B→A→D dominates S→A→D and

S→B→D

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Mediated Prisoners Dilemma

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Cooperate Defect

Cooperatex 1, 1 5, 0

Defectx 0, 5 3, 3

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Mediated Game

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Mediator Cooperate Defect

Mediatorx

Cooperatex 1, 1 5, 0

Defectx 0, 5 3, 3

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Mediated Game

55

Mediator Cooperate Defect

Mediatorx 2, 2

Cooperatex 1, 1 5, 0

Defectx 2, 2 0, 5 3, 3

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Mediated Game

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Mediator Cooperate Defect

Mediatorx 0, 5 2, 2

Cooperatex 5, 0 1, 1 5, 0

Defectx 2, 2 0, 5 3, 3

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Mediated Game

57

Mediator Cooperate Defect

Mediatorx 1, 1 0, 5 2, 2

Cooperatex 5, 0 1, 1 5, 0

Defectx 2, 2 0, 5 3, 3

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Mediated Equilibrium

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Mediator Cooperate Defect

Mediatorx 1, 1 0, 5 2, 2

Cooperatex 5, 0 1, 1 5, 0

Defectx 2, 2 0, 5 3, 3