Game Theory: Normal Form Games

Size: px
Start display at page:

Download "Game Theory: Normal Form Games"

Transcription

1 Game Theory: Normal Form Games CPSC 322 Lecture 34 April 3, 2006 Reading: excerpt from Multiagent Systems, chapter 3. Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 1

2 Lecture Overview Recap Game Theory Example Matrix Games Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 2

3 Rewards and Values Suppose the agent receives the sequence of rewards r 1, r 2, r 3, r 4,.... What value should be assigned? total reward V = i=1 r i average reward V = lim n discounted reward V = r r n n i=1 γi 1 r i γ is the discount factor 0 γ 1 Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 3

4 Policies A stationary policy is a function: π : S A Given a state s, π(s) specifies what action the agent who is following π will do. An optimal policy is one with maximum expected value we ll focus on the case where value is defined as discounted reward. For an MDP with stationary dynamics and rewards with infinite or indefinite horizon, there is always an optimal stationary policy in this case. Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 4

5 Value of a Policy Q π (s, a), where a is an action and s is a state, is the expected value of doing a in state s, then following policy π. V π (s), where s is a state, is the expected value of following policy π in state s. Q π and V π can be defined mutually recursively: V π (s) = Q π (s, π(s)) Q π (s, a) = s P (s a, s) ( r(s, a, s ) + γv π (s ) ) Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 5

6 Value of the Optimal Policy Q (s, a), where a is an action and s is a state, is the expected value of doing a in state s, then following the optimal policy. V (s), where s is a state, is the expected value of following the optimal policy in state s. Q and V can be defined mutually recursively: Q (s, a) = s P (s a, s) ( r(s, a, s ) + γv (s ) ) V (s) = max Q (s, a) a π (s) = arg max Q (s, a) a Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 6

7 Value Iteration Idea: Given an estimate of the k-step lookahead value function, determine the k + 1 step lookahead value function. Set V 0 arbitrarily. e.g., zeros Compute Q i+1 and V i+1 from V i : Q i+1 (s, a) = s P (s a, s) ( r(s, a, s ) + γv i (s ) ) V i+1 (s) = max Q i+1 (s, a) a If we intersect these equations at Q i+1, we get an update equation for V : V i+1 (s) = max P (s ( a, s) r(s, a, s ) + γv i (s ) ) a s Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 7

8 Asynchronous VI: storing Q[s, a] Repeat forever: Select state s, action a; ( ) Q[s, a] P (s s, a) R(s, a, s ) + γ max Q[s, a ] ; a s Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 8

9 Lecture Overview Recap Game Theory Example Matrix Games Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 9

10 Non-Cooperative Game Theory What is it? Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 10

11 Non-Cooperative Game Theory What is it? mathematical study of interaction between rational, self-interested agents Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 10

12 Non-Cooperative Game Theory What is it? mathematical study of interaction between rational, self-interested agents Why is it called non-cooperative? Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 10

13 Non-Cooperative Game Theory What is it? mathematical study of interaction between rational, self-interested agents Why is it called non-cooperative? while it s most interested in situations where agents interests conflict, it s not restricted to these settings the key is that the individual is the basic modeling unit, and that individuals pursue their own interests cooperative/coalitional game theory has teams as the central unit, rather than agents You can think of a non-cooperative game as a decision diagram where different agents control different decision nodes, and where each agent has his own utility node. Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 10

14 TCP Backoff Game Should you send your packets using correctly-implemented TCP (which has a backoff mechanism) or using a defective implementation (which doesn t)? 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. Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 11

15 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. 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? Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 11

16 Defining Games Finite, n-person game: N, A, u : N is a finite set of n players, indexed by i A = A1,..., A n is a set of actions for each player i a A is an action profile u = {u 1,..., u n }, a utility function for each player, where u i : A R Writing a 2-player game as a matrix: row player is player 1, column player is player 2 rows are actions a A1, columns are a A 2 cells are outcomes, written as a tuple of utility values for each player Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 12

17 Lecture Overview Recap Game Theory Example Matrix Games Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 13

18 d D (for using a Defective one). If both you and your colleague verage packet delay is 1ms (millisecond). If you both adopt D the segames of additional in Matrix overhead at Form the network router. Finally, if one of e other adopts C then the D adopter will experience no delay at all, ill experience a delay of 4ms. ces arehere s shownthe in Figure TCP Backoff 3.1. YourGame options written are theas two a matrix rows, and ( normal form ) tions are andthe ascolumns. a decisionin network. each cell, the first number represents us your delay), and the second number represents your colleague s Recap Game Theory Example Matrix Games C D Action by Player 1 Action by Player 2 C 1, 1 4,0 D 0, 4 3, 3 P1 Utility P2 Utility ure 3.1 The TCP user s (aka the Prisoner s) Dilemma. ns what should you adopt, C or D? Does it depend on what you e will do? Furthermore, from the perspective of the network operaavior can he expect from the two users? Will any two users behave Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 14

19 d D (for using a Defective one). If both you and your colleague verage packet delay is 1ms (millisecond). If you both adopt D the segames of additional in Matrix overhead at Form the network router. Finally, if one of e other adopts C then the D adopter will experience no delay at all, ill experience a delay of 4ms. ces arehere s shownthe in Figure TCP Backoff 3.1. YourGame options written are theas two a matrix rows, and ( normal form ) tions are andthe ascolumns. a decisionin network. each cell, the first number represents us your delay), and the second number represents your colleague s Recap Game Theory Example Matrix Games C D Action by Player 1 Action by Player 2 C 1, 1 4,0 D 0, 4 3, 3 P1 Utility P2 Utility ure 3.1 The TCP user s (aka the Prisoner s) Dilemma. Play this game with someone near you, repeating five times. ns what should you adopt, C or D? Does it depend on what you e will do? Furthermore, from the perspective of the network operaavior can he expect from the two users? Will any two users behave Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 14

20 More General Form 3 Competition and Coordination: Normal form games Prisoner s dilemma is any game C D C a,a b,c D c,b d,d Figure 3.3 Any c > a > d > b define an instance of Prisoner s Dilemma. with c > a > d > b. To fully understand the role of the payoff numbers we would need to enter into a discussion of utility theory. Here, let us just mention that for most purposes, the analysis of any game is unchanged if the payoff numbers undergo any positive affine Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 15

21 Games of Pure Competition Players have exactly opposed interests There must be precisely two players (otherwise they can t have exactly opposed interests) For all action profiles a A, u 1 (a) + u 2 (a) = c for some constant c Special case: zero sum Thus, we only need to store a utility function for one player Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 16

22 the abbreviation we must explicit state whether this matrix represents a common-payoff game or a zero-sum one. Matching A classical Pennies example of a zero-sum game is the game of matching pennies. In this game, each of the two players has a penny, and independently chooses to display either heads or tails. The two players then compare their pennies. If they are the same then player 1 pockets both, and otherwise player 2 pockets them. The payoff matrix is shown One in Figure player 3.5. wants to match; the other wants to mismatch. Heads Tails Heads 1 1 Tails 1 1 Figure 3.5 Matching Pennies game. The popular children s game of Rock, Paper, Scissors, also known as Rochambeau, provides a three-strategy generalization of the matching-pennies game. The payoff matrix of this zero-sum game is shown in Figure 3.6. In this game, each of the two players can choose either Rock, Paper, or Scissors. If both players choose the same Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 17

23 the abbreviation we must explicit state whether this matrix represents a common-payoff game or a zero-sum one. Matching A classical Pennies example of a zero-sum game is the game of matching pennies. In this game, each of the two players has a penny, and independently chooses to display either heads or tails. The two players then compare their pennies. If they are the same then player 1 pockets both, and otherwise player 2 pockets them. The payoff matrix is shown One in Figure player 3.5. wants to match; the other wants to mismatch. Heads Tails Heads 1 1 Tails 1 1 Figure 3.5 Matching Pennies game. Play this game with someone near you, repeating five times. The popular children s game of Rock, Paper, Scissors, also known as Rochambeau, provides a three-strategy generalization of the matching-pennies game. The payoff matrix of this zero-sum game is shown in Figure 3.6. In this game, each of the two players can choose either Rock, Paper, or Scissors. If both players choose the same Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 17

24 Rock-Paper-Scissors 3 Competition and Coordination: Normal form games Generalized matching pennies. Rock Paper Scissors Rock Paper Scissors Figure 3.6 Rock, Paper, Scissors game....believe it or not, there s an annual international competition for this game! VG GL VG 2,1 0,0 Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 18

25 Games of Cooperation Players have exactly the same interests. no conflict: all players want the same things a A, i, j, u i (a) = u j (a) we often write such games with a single payoff per cell why are such games noncooperative? Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 19

26 Game Theory: Normal Form Games c Shoham and Leyton-Brown, 2006 CPSC 322 Lecture 34, Slide 20 the agents have no conflicting interests; their sole challenge is to coordinate on an Recap Game Theory Example Matrix Games action that is maximally beneficial to all. Coordination Because of theirgame special nature, we often represent common value games with an abbreviated form of the matrix in which we list only one payoff in each of the cells. As an example, imagine two drivers driving towards each other in a country without traffic rules, and who must independently decide whether to drive on the left or on the right. If the players choose the same side (left or right) they have some high utility, and otherwise Which they side have ofathe lowroad utility. should The game you matrix drive on? is shown in Figure 3.4. Left Right Left 1 0 Right 0 1 Figure 3.4 Coordination game. At the other end of the spectrum from pure coordination games lie zero-sum games, which (bearing in mind the comment we made earlier about positive affine transformations) are more properly called constant-sum games. Unlike common-payoff games,

27 the agents have no conflicting interests; their sole challenge is to coordinate on an Recap Game Theory Example Matrix Games action that is maximally beneficial to all. Coordination Because of theirgame special nature, we often represent common value games with an abbreviated form of the matrix in which we list only one payoff in each of the cells. As an example, imagine two drivers driving towards each other in a country without traffic rules, and who must independently decide whether to drive on the left or on the right. If the players choose the same side (left or right) they have some high utility, and otherwise Which they side have ofathe lowroad utility. should The game you matrix drive on? is shown in Figure 3.4. Left Right Left 1 0 Right 0 1 Figure 3.4 Coordination game. Play this game with someone near you, repeating five times. At the other end of the spectrum from pure coordination games lie zero-sum games, which (bearing in mind the comment we made earlier about positive affine transformations) are more properly called constant-sum games. Unlike common-payoff games, c Shoham and Leyton-Brown, 2006 Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 20

28 Rock Recap Game Theory Example Matrix Games We have so far defined the actions available to each player in a game, but not yet his Game set of Theory: strategies, Normal FormorGames his available choices. Certainly one kind of CPSC strategy 322 Lecture is to 34, select Slide 21 General Games: Battle of the Sexes Paper Scissors The most interesting games combine elements of cooperation and competition. Figure 3.6 Rock, Paper, Scissors game. B F B 2,1 0,0 F 0,0 1,2 Figure 3.7 Battle of the Sexes game. Strategies in normal-form games

29 Rock Recap Game Theory Example Matrix Games General Games: Battle of the Sexes Paper Scissors The most interesting games combine elements of cooperation and competition. Figure 3.6 Rock, Paper, Scissors game. B F B 2,1 0,0 F 0,0 1,2 Figure 3.7 Battle of the Sexes game. Play this game with someone near you, repeating five times. Strategies in normal-form games We have so far defined the actions available to each player in a game, but not yet his set of strategies, or his available choices. Certainly one kind of strategy is to select Game Theory: Normal Form Games CPSC 322 Lecture 34, Slide 21

Game Theory Intro. Lecture 3. Game Theory Intro Lecture 3, Slide 1

Game Theory Intro. Lecture 3. Game Theory Intro Lecture 3, Slide 1 Game Theory Intro Lecture 3 Game Theory Intro Lecture 3, Slide 1 Lecture Overview 1 What is Game Theory? 2 Game Theory Intro Lecture 3, Slide 2 Non-Cooperative Game Theory What is it? Game Theory Intro

More information

Self-interested agents What is Game Theory? Example Matrix Games. Game Theory Intro. Lecture 3. Game Theory Intro Lecture 3, Slide 1

Self-interested agents What is Game Theory? Example Matrix Games. Game Theory Intro. Lecture 3. Game Theory Intro Lecture 3, Slide 1 Game Theory Intro Lecture 3 Game Theory Intro Lecture 3, Slide 1 Lecture Overview 1 Self-interested agents 2 What is Game Theory? 3 Example Matrix Games Game Theory Intro Lecture 3, Slide 2 Self-interested

More information

Game Theory Week 1. Game Theory Course: Jackson, Leyton-Brown & Shoham. Game Theory Course: Jackson, Leyton-Brown & Shoham Game Theory Week 1

Game Theory Week 1. Game Theory Course: Jackson, Leyton-Brown & Shoham. Game Theory Course: Jackson, Leyton-Brown & Shoham Game Theory Week 1 Game Theory Week 1 Game Theory Course: Jackson, Leyton-Brown & Shoham A Flipped Classroom Course Before Tuesday class: Watch the week s videos, on Coursera or locally at UBC Hand in the previous week s

More information

Analyzing Games: Mixed Strategies

Analyzing Games: Mixed Strategies Analyzing Games: Mixed Strategies CPSC 532A Lecture 5 September 26, 2006 Analyzing Games: Mixed Strategies CPSC 532A Lecture 5, Slide 1 Lecture Overview Recap Mixed Strategies Fun Game Analyzing Games:

More information

ESSENTIALS OF GAME THEORY

ESSENTIALS OF GAME THEORY ESSENTIALS OF GAME THEORY 1 CHAPTER 1 Games in Normal Form Game theory studies what happens when self-interested agents interact. What does it mean to say that agents are self-interested? It does not necessarily

More information

Mixed Strategies; Maxmin

Mixed Strategies; Maxmin Mixed Strategies; Maxmin CPSC 532A Lecture 4 January 28, 2008 Mixed Strategies; Maxmin CPSC 532A Lecture 4, Slide 1 Lecture Overview 1 Recap 2 Mixed Strategies 3 Fun Game 4 Maxmin and Minmax Mixed Strategies;

More information

Computing Nash Equilibrium; Maxmin

Computing Nash Equilibrium; Maxmin Computing Nash Equilibrium; Maxmin Lecture 5 Computing Nash Equilibrium; Maxmin Lecture 5, Slide 1 Lecture Overview 1 Recap 2 Computing Mixed Nash Equilibria 3 Fun Game 4 Maxmin and Minmax Computing Nash

More information

CS510 \ Lecture Ariel Stolerman

CS510 \ Lecture Ariel Stolerman CS510 \ Lecture04 2012-10-15 1 Ariel Stolerman Administration Assignment 2: just a programming assignment. Midterm: posted by next week (5), will cover: o Lectures o Readings A midterm review sheet will

More information

Domination Rationalizability Correlated Equilibrium Computing CE Computational problems in domination. Game Theory Week 3. Kevin Leyton-Brown

Domination Rationalizability Correlated Equilibrium Computing CE Computational problems in domination. Game Theory Week 3. Kevin Leyton-Brown Game Theory Week 3 Kevin Leyton-Brown Game Theory Week 3 Kevin Leyton-Brown, Slide 1 Lecture Overview 1 Domination 2 Rationalizability 3 Correlated Equilibrium 4 Computing CE 5 Computational problems in

More information

Chapter 3 Learning in Two-Player Matrix Games

Chapter 3 Learning in Two-Player Matrix Games Chapter 3 Learning in Two-Player Matrix Games 3.1 Matrix Games In this chapter, we will examine the two-player stage game or the matrix game problem. Now, we have two players each learning how to play

More information

Noncooperative Games COMP4418 Knowledge Representation and Reasoning

Noncooperative Games COMP4418 Knowledge Representation and Reasoning Noncooperative Games COMP4418 Knowledge Representation and Reasoning Abdallah Saffidine 1 1 abdallah.saffidine@gmail.com slides design: Haris Aziz Semester 2, 2017 Abdallah Saffidine (UNSW) Noncooperative

More information

Dominant Strategies (From Last Time)

Dominant Strategies (From Last Time) Dominant Strategies (From Last Time) Continue eliminating dominated strategies for B and A until you narrow down how the game is actually played. What strategies should A and B choose? How are these the

More information

Microeconomics of Banking: Lecture 4

Microeconomics of Banking: Lecture 4 Microeconomics of Banking: Lecture 4 Prof. Ronaldo CARPIO Oct. 16, 2015 Administrative Stuff Homework 1 is due today at the end of class. I will upload the solutions and Homework 2 (due in two weeks) later

More information

CMU-Q Lecture 20:

CMU-Q Lecture 20: CMU-Q 15-381 Lecture 20: Game Theory I Teacher: Gianni A. Di Caro ICE-CREAM WARS http://youtu.be/jilgxenbk_8 2 GAME THEORY Game theory is the formal study of conflict and cooperation in (rational) multi-agent

More information

Reading Robert Gibbons, A Primer in Game Theory, Harvester Wheatsheaf 1992.

Reading Robert Gibbons, A Primer in Game Theory, Harvester Wheatsheaf 1992. Reading Robert Gibbons, A Primer in Game Theory, Harvester Wheatsheaf 1992. Additional readings could be assigned from time to time. They are an integral part of the class and you are expected to read

More information

Dominance and Best Response. player 2

Dominance and Best Response. player 2 Dominance and Best Response Consider the following game, Figure 6.1(a) from the text. player 2 L R player 1 U 2, 3 5, 0 D 1, 0 4, 3 Suppose you are player 1. The strategy U yields higher payoff than any

More information

CSCI 699: Topics in Learning and Game Theory Fall 2017 Lecture 3: Intro to Game Theory. Instructor: Shaddin Dughmi

CSCI 699: Topics in Learning and Game Theory Fall 2017 Lecture 3: Intro to Game Theory. Instructor: Shaddin Dughmi CSCI 699: Topics in Learning and Game Theory Fall 217 Lecture 3: Intro to Game Theory Instructor: Shaddin Dughmi Outline 1 Introduction 2 Games of Complete Information 3 Games of Incomplete Information

More information

Game Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India August 2012

Game Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India August 2012 Game Theory Lecture Notes By Y. Narahari Department of Computer Science and Automation Indian Institute of Science Bangalore, India August 01 Rationalizable Strategies Note: This is a only a draft version,

More information

Advanced Microeconomics (Economics 104) Spring 2011 Strategic games I

Advanced Microeconomics (Economics 104) Spring 2011 Strategic games I Advanced Microeconomics (Economics 104) Spring 2011 Strategic games I Topics The required readings for this part is O chapter 2 and further readings are OR 2.1-2.3. The prerequisites are the Introduction

More information

Dominant and Dominated Strategies

Dominant and Dominated Strategies Dominant and Dominated Strategies Carlos Hurtado Department of Economics University of Illinois at Urbana-Champaign hrtdmrt2@illinois.edu Junel 8th, 2016 C. Hurtado (UIUC - Economics) Game Theory On the

More information

Minmax and Dominance

Minmax and Dominance Minmax and Dominance CPSC 532A Lecture 6 September 28, 2006 Minmax and Dominance CPSC 532A Lecture 6, Slide 1 Lecture Overview Recap Maxmin and Minmax Linear Programming Computing Fun Game Domination Minmax

More information

Game Theory: The Basics. Theory of Games and Economics Behavior John Von Neumann and Oskar Morgenstern (1943)

Game Theory: The Basics. Theory of Games and Economics Behavior John Von Neumann and Oskar Morgenstern (1943) Game Theory: The Basics The following is based on Games of Strategy, Dixit and Skeath, 1999. Topic 8 Game Theory Page 1 Theory of Games and Economics Behavior John Von Neumann and Oskar Morgenstern (1943)

More information

Repeated Games. ISCI 330 Lecture 16. March 13, Repeated Games ISCI 330 Lecture 16, Slide 1

Repeated Games. ISCI 330 Lecture 16. March 13, Repeated Games ISCI 330 Lecture 16, Slide 1 Repeated Games ISCI 330 Lecture 16 March 13, 2007 Repeated Games ISCI 330 Lecture 16, Slide 1 Lecture Overview Repeated Games ISCI 330 Lecture 16, Slide 2 Intro Up to this point, in our discussion of extensive-form

More information

U strictly dominates D for player A, and L strictly dominates R for player B. This leaves (U, L) as a Strict Dominant Strategy Equilibrium.

U strictly dominates D for player A, and L strictly dominates R for player B. This leaves (U, L) as a Strict Dominant Strategy Equilibrium. Problem Set 3 (Game Theory) Do five of nine. 1. Games in Strategic Form Underline all best responses, then perform iterated deletion of strictly dominated strategies. In each case, do you get a unique

More information

Game Theory. Wolfgang Frimmel. Dominance

Game Theory. Wolfgang Frimmel. Dominance Game Theory Wolfgang Frimmel Dominance 1 / 13 Example: Prisoners dilemma Consider the following game in normal-form: There are two players who both have the options cooperate (C) and defect (D) Both players

More information

Section Notes 6. Game Theory. Applied Math 121. Week of March 22, understand the difference between pure and mixed strategies.

Section Notes 6. Game Theory. Applied Math 121. Week of March 22, understand the difference between pure and mixed strategies. Section Notes 6 Game Theory Applied Math 121 Week of March 22, 2010 Goals for the week be comfortable with the elements of game theory. understand the difference between pure and mixed strategies. be able

More information

LECTURE 26: GAME THEORY 1

LECTURE 26: GAME THEORY 1 15-382 COLLECTIVE INTELLIGENCE S18 LECTURE 26: GAME THEORY 1 INSTRUCTOR: GIANNI A. DI CARO ICE-CREAM WARS http://youtu.be/jilgxenbk_8 2 GAME THEORY Game theory is the formal study of conflict and cooperation

More information

Multi-player, non-zero-sum games

Multi-player, non-zero-sum games Multi-player, non-zero-sum games 4,3,2 4,3,2 1,5,2 4,3,2 7,4,1 1,5,2 7,7,1 Utilities are tuples Each player maximizes their own utility at each node Utilities get propagated (backed up) from children to

More information

Lecture 6: Basics of Game Theory

Lecture 6: Basics of Game Theory 0368.4170: Cryptography and Game Theory Ran Canetti and Alon Rosen Lecture 6: Basics of Game Theory 25 November 2009 Fall 2009 Scribes: D. Teshler Lecture Overview 1. What is a Game? 2. Solution Concepts:

More information

Game Tree Search. CSC384: Introduction to Artificial Intelligence. Generalizing Search Problem. General Games. What makes something a game?

Game Tree Search. CSC384: Introduction to Artificial Intelligence. Generalizing Search Problem. General Games. What makes something a game? CSC384: Introduction to Artificial Intelligence Generalizing Search Problem Game Tree Search Chapter 5.1, 5.2, 5.3, 5.6 cover some of the material we cover here. Section 5.6 has an interesting overview

More information

CMU Lecture 22: Game Theory I. Teachers: Gianni A. Di Caro

CMU Lecture 22: Game Theory I. Teachers: Gianni A. Di Caro CMU 15-781 Lecture 22: Game Theory I Teachers: Gianni A. Di Caro GAME THEORY Game theory is the formal study of conflict and cooperation in (rational) multi-agent systems Decision-making where several

More information

Game Theory ( nd term) Dr. S. Farshad Fatemi. Graduate School of Management and Economics Sharif University of Technology.

Game Theory ( nd term) Dr. S. Farshad Fatemi. Graduate School of Management and Economics Sharif University of Technology. Game Theory 44812 (1393-94 2 nd term) Dr. S. Farshad Fatemi Graduate School of Management and Economics Sharif University of Technology Spring 2015 Dr. S. Farshad Fatemi (GSME) Game Theory Spring 2015

More information

Math 464: Linear Optimization and Game

Math 464: Linear Optimization and Game Math 464: Linear Optimization and Game Haijun Li Department of Mathematics Washington State University Spring 2013 Game Theory Game theory (GT) is a theory of rational behavior of people with nonidentical

More information

Multiagent Systems: Intro to Game Theory. CS 486/686: Introduction to Artificial Intelligence

Multiagent Systems: Intro to Game Theory. CS 486/686: Introduction to Artificial Intelligence Multiagent Systems: Intro to Game Theory CS 486/686: Introduction to Artificial Intelligence 1 Introduction So far almost everything we have looked at has been in a single-agent setting Today - Multiagent

More information

(a) Left Right (b) Left Right. Up Up 5-4. Row Down 0-5 Row Down 1 2. (c) B1 B2 (d) B1 B2 A1 4, 2-5, 6 A1 3, 2 0, 1

(a) Left Right (b) Left Right. Up Up 5-4. Row Down 0-5 Row Down 1 2. (c) B1 B2 (d) B1 B2 A1 4, 2-5, 6 A1 3, 2 0, 1 Economics 109 Practice Problems 2, Vincent Crawford, Spring 2002 In addition to these problems and those in Practice Problems 1 and the midterm, you may find the problems in Dixit and Skeath, Games of

More information

Game theory attempts to mathematically. capture behavior in strategic situations, or. games, in which an individual s success in

Game theory attempts to mathematically. capture behavior in strategic situations, or. games, in which an individual s success in Game Theory Game theory attempts to mathematically capture behavior in strategic situations, or games, in which an individual s success in making choices depends on the choices of others. A game Γ consists

More information

Math 152: Applicable Mathematics and Computing

Math 152: Applicable Mathematics and Computing Math 152: Applicable Mathematics and Computing April 16, 2017 April 16, 2017 1 / 17 Announcements Please bring a blue book for the midterm on Friday. Some students will be taking the exam in Center 201,

More information

1. Introduction to Game Theory

1. Introduction to Game Theory 1. Introduction to Game Theory What is game theory? Important branch of applied mathematics / economics Eight game theorists have won the Nobel prize, most notably John Nash (subject of Beautiful mind

More information

1. Simultaneous games All players move at same time. Represent with a game table. We ll stick to 2 players, generally A and B or Row and Col.

1. Simultaneous games All players move at same time. Represent with a game table. We ll stick to 2 players, generally A and B or Row and Col. I. Game Theory: Basic Concepts 1. Simultaneous games All players move at same time. Represent with a game table. We ll stick to 2 players, generally A and B or Row and Col. Representation of utilities/preferences

More information

ECON 282 Final Practice Problems

ECON 282 Final Practice Problems ECON 282 Final Practice Problems S. Lu Multiple Choice Questions Note: The presence of these practice questions does not imply that there will be any multiple choice questions on the final exam. 1. How

More information

1\2 L m R M 2, 2 1, 1 0, 0 B 1, 0 0, 0 1, 1

1\2 L m R M 2, 2 1, 1 0, 0 B 1, 0 0, 0 1, 1 Chapter 1 Introduction Game Theory is a misnomer for Multiperson Decision Theory. It develops tools, methods, and language that allow a coherent analysis of the decision-making processes when there are

More information

Introduction to (Networked) Game Theory. Networked Life NETS 112 Fall 2016 Prof. Michael Kearns

Introduction to (Networked) Game Theory. Networked Life NETS 112 Fall 2016 Prof. Michael Kearns Introduction to (Networked) Game Theory Networked Life NETS 112 Fall 2016 Prof. Michael Kearns Game Theory for Fun and Profit The Beauty Contest Game Write your name and an integer between 0 and 100 Let

More information

Repeated Games. Economics Microeconomic Theory II: Strategic Behavior. Shih En Lu. Simon Fraser University (with thanks to Anke Kessler)

Repeated Games. Economics Microeconomic Theory II: Strategic Behavior. Shih En Lu. Simon Fraser University (with thanks to Anke Kessler) Repeated Games Economics 302 - Microeconomic Theory II: Strategic Behavior Shih En Lu Simon Fraser University (with thanks to Anke Kessler) ECON 302 (SFU) Repeated Games 1 / 25 Topics 1 Information Sets

More information

NORMAL FORM (SIMULTANEOUS MOVE) GAMES

NORMAL FORM (SIMULTANEOUS MOVE) GAMES NORMAL FORM (SIMULTANEOUS MOVE) GAMES 1 For These Games Choices are simultaneous made independently and without observing the other players actions Players have complete information, which means they know

More information

Game Theory and Randomized Algorithms

Game Theory and Randomized Algorithms Game Theory and Randomized Algorithms Guy Aridor Game theory is a set of tools that allow us to understand how decisionmakers interact with each other. It has practical applications in economics, international

More information

Game Theory. Department of Electronics EL-766 Spring Hasan Mahmood

Game Theory. Department of Electronics EL-766 Spring Hasan Mahmood Game Theory Department of Electronics EL-766 Spring 2011 Hasan Mahmood Email: hasannj@yahoo.com Course Information Part I: Introduction to Game Theory Introduction to game theory, games with perfect information,

More information

Basic Solution Concepts and Computational Issues

Basic Solution Concepts and Computational Issues CHAPTER asic Solution Concepts and Computational Issues Éva Tardos and Vijay V. Vazirani Abstract We consider some classical games and show how they can arise in the context of the Internet. We also introduce

More information

Problem 1 (15 points: Graded by Shahin) Recall the network structure of our in-class trading experiment shown in Figure 1

Problem 1 (15 points: Graded by Shahin) Recall the network structure of our in-class trading experiment shown in Figure 1 Solutions for Homework 2 Networked Life, Fall 204 Prof Michael Kearns Due as hardcopy at the start of class, Tuesday December 9 Problem (5 points: Graded by Shahin) Recall the network structure of our

More information

Finite games: finite number of players, finite number of possible actions, finite number of moves. Canusegametreetodepicttheextensiveform.

Finite games: finite number of players, finite number of possible actions, finite number of moves. Canusegametreetodepicttheextensiveform. A game is a formal representation of a situation in which individuals interact in a setting of strategic interdependence. Strategic interdependence each individual s utility depends not only on his own

More information

First Prev Next Last Go Back Full Screen Close Quit. Game Theory. Giorgio Fagiolo

First Prev Next Last Go Back Full Screen Close Quit. Game Theory. Giorgio Fagiolo Game Theory Giorgio Fagiolo giorgio.fagiolo@univr.it https://mail.sssup.it/ fagiolo/welcome.html Academic Year 2005-2006 University of Verona Web Resources My homepage: https://mail.sssup.it/~fagiolo/welcome.html

More information

ECON 312: Games and Strategy 1. Industrial Organization Games and Strategy

ECON 312: Games and Strategy 1. Industrial Organization Games and Strategy ECON 312: Games and Strategy 1 Industrial Organization Games and Strategy A Game is a stylized model that depicts situation of strategic behavior, where the payoff for one agent depends on its own actions

More information

Topic 1: defining games and strategies. SF2972: Game theory. Not allowed: Extensive form game: formal definition

Topic 1: defining games and strategies. SF2972: Game theory. Not allowed: Extensive form game: formal definition SF2972: Game theory Mark Voorneveld, mark.voorneveld@hhs.se Topic 1: defining games and strategies Drawing a game tree is usually the most informative way to represent an extensive form game. Here is one

More information

Adversarial Search and Game Theory. CS 510 Lecture 5 October 26, 2017

Adversarial Search and Game Theory. CS 510 Lecture 5 October 26, 2017 Adversarial Search and Game Theory CS 510 Lecture 5 October 26, 2017 Reminders Proposals due today Midterm next week past midterms online Midterm online BBLearn Available Thurs-Sun, ~2 hours Overview Game

More information

CS188: Artificial Intelligence, Fall 2011 Written 2: Games and MDP s

CS188: Artificial Intelligence, Fall 2011 Written 2: Games and MDP s CS88: Artificial Intelligence, Fall 20 Written 2: Games and MDP s Due: 0/5 submitted electronically by :59pm (no slip days) Policy: Can be solved in groups (acknowledge collaborators) but must be written

More information

ECO 220 Game Theory. Objectives. Agenda. Simultaneous Move Games. Be able to structure a game in normal form Be able to identify a Nash equilibrium

ECO 220 Game Theory. Objectives. Agenda. Simultaneous Move Games. Be able to structure a game in normal form Be able to identify a Nash equilibrium ECO 220 Game Theory Simultaneous Move Games Objectives Be able to structure a game in normal form Be able to identify a Nash equilibrium Agenda Definitions Equilibrium Concepts Dominance Coordination Games

More information

GAME THEORY: STRATEGY AND EQUILIBRIUM

GAME THEORY: STRATEGY AND EQUILIBRIUM Prerequisites Almost essential Game Theory: Basics GAME THEORY: STRATEGY AND EQUILIBRIUM MICROECONOMICS Principles and Analysis Frank Cowell Note: the detail in slides marked * can only be seen if you

More information

Lecture 23. Offense vs. Defense & Dynamic Games

Lecture 23. Offense vs. Defense & Dynamic Games Lecture 3. Offense vs. Defense & Dynamic Games EC DD & EE / Manove Offense vs Defense p EC DD & EE / Manove Clicker Question p Using Game Theory to Analyze Offense versus Defense In many competitive situations

More information

Dominant and Dominated Strategies

Dominant and Dominated Strategies Dominant and Dominated Strategies Carlos Hurtado Department of Economics University of Illinois at Urbana-Champaign hrtdmrt2@illinois.edu May 29th, 2015 C. Hurtado (UIUC - Economics) Game Theory On the

More information

Game theory. Logic and Decision Making Unit 2

Game theory. Logic and Decision Making Unit 2 Game theory Logic and Decision Making Unit 2 Introduction Game theory studies decisions in which the outcome depends (at least partly) on what other people do All decision makers are assumed to possess

More information

Lecture Notes on Game Theory (QTM)

Lecture Notes on Game Theory (QTM) Theory of games: Introduction and basic terminology, pure strategy games (including identification of saddle point and value of the game), Principle of dominance, mixed strategy games (only arithmetic

More information

14.12 Game Theory Lecture Notes Lectures 10-11

14.12 Game Theory Lecture Notes Lectures 10-11 4.2 Game Theory Lecture Notes Lectures 0- Muhamet Yildiz Repeated Games In these notes, we ll discuss the repeated games, the games where a particular smaller game is repeated; the small game is called

More information

UPenn NETS 412: Algorithmic Game Theory Game Theory Practice. Clyde Silent Confess Silent 1, 1 10, 0 Confess 0, 10 5, 5

UPenn NETS 412: Algorithmic Game Theory Game Theory Practice. Clyde Silent Confess Silent 1, 1 10, 0 Confess 0, 10 5, 5 Problem 1 UPenn NETS 412: Algorithmic Game Theory Game Theory Practice Bonnie Clyde Silent Confess Silent 1, 1 10, 0 Confess 0, 10 5, 5 This game is called Prisoner s Dilemma. Bonnie and Clyde have been

More information

Game Tree Search. Generalizing Search Problems. Two-person Zero-Sum Games. Generalizing Search Problems. CSC384: Intro to Artificial Intelligence

Game Tree Search. Generalizing Search Problems. Two-person Zero-Sum Games. Generalizing Search Problems. CSC384: Intro to Artificial Intelligence CSC384: Intro to Artificial Intelligence Game Tree Search Chapter 6.1, 6.2, 6.3, 6.6 cover some of the material we cover here. Section 6.6 has an interesting overview of State-of-the-Art game playing programs.

More information

EC3224 Autumn Lecture #02 Nash Equilibrium

EC3224 Autumn Lecture #02 Nash Equilibrium Reading EC3224 Autumn Lecture #02 Nash Equilibrium Osborne Chapters 2.6-2.10, (12) By the end of this week you should be able to: define Nash equilibrium and explain several different motivations for it.

More information

Game Theory: introduction and applications to computer networks

Game Theory: introduction and applications to computer networks Game Theory: introduction and applications to computer networks Lecture 1: introduction Giovanni Neglia INRIA EPI Maestro 30 January 2012 Part of the slides are based on a previous course with D. Figueiredo

More information

CSC384: Introduction to Artificial Intelligence. Game Tree Search

CSC384: Introduction to Artificial Intelligence. Game Tree Search CSC384: Introduction to Artificial Intelligence Game Tree Search Chapter 5.1, 5.2, 5.3, 5.6 cover some of the material we cover here. Section 5.6 has an interesting overview of State-of-the-Art game playing

More information

ECON 2100 Principles of Microeconomics (Summer 2016) Game Theory and Oligopoly

ECON 2100 Principles of Microeconomics (Summer 2016) Game Theory and Oligopoly ECON 2100 Principles of Microeconomics (Summer 2016) Game Theory and Oligopoly Relevant readings from the textbook: Mankiw, Ch. 17 Oligopoly Suggested problems from the textbook: Chapter 17 Questions for

More information

Resource Allocation and Decision Analysis (ECON 8010) Spring 2014 Foundations of Game Theory

Resource Allocation and Decision Analysis (ECON 8010) Spring 2014 Foundations of Game Theory Resource Allocation and Decision Analysis (ECON 8) Spring 4 Foundations of Game Theory Reading: Game Theory (ECON 8 Coursepak, Page 95) Definitions and Concepts: Game Theory study of decision making settings

More information

Introduction to (Networked) Game Theory. Networked Life NETS 112 Fall 2014 Prof. Michael Kearns

Introduction to (Networked) Game Theory. Networked Life NETS 112 Fall 2014 Prof. Michael Kearns Introduction to (Networked) Game Theory Networked Life NETS 112 Fall 2014 Prof. Michael Kearns percent who will actually attend 100% Attendance Dynamics: Concave equilibrium: 100% percent expected to attend

More information

Extensive Form Games: Backward Induction and Imperfect Information Games

Extensive Form Games: Backward Induction and Imperfect Information Games Extensive Form Games: Backward Induction and Imperfect Information Games CPSC 532A Lecture 10 October 12, 2006 Extensive Form Games: Backward Induction and Imperfect Information Games CPSC 532A Lecture

More information

FIRST PART: (Nash) Equilibria

FIRST PART: (Nash) Equilibria FIRST PART: (Nash) Equilibria (Some) Types of games Cooperative/Non-cooperative Symmetric/Asymmetric (for 2-player games) Zero sum/non-zero sum Simultaneous/Sequential Perfect information/imperfect information

More information

3 Game Theory II: Sequential-Move and Repeated Games

3 Game Theory II: Sequential-Move and Repeated Games 3 Game Theory II: Sequential-Move and Repeated Games Recognizing that the contributions you make to a shared computer cluster today will be known to other participants tomorrow, you wonder how that affects

More information

Lecture 10: September 2

Lecture 10: September 2 SC 63: Games and Information Autumn 24 Lecture : September 2 Instructor: Ankur A. Kulkarni Scribes: Arjun N, Arun, Rakesh, Vishal, Subir Note: LaTeX template courtesy of UC Berkeley EECS dept. Disclaimer:

More information

Computational Methods for Non-Cooperative Game Theory

Computational Methods for Non-Cooperative Game Theory Computational Methods for Non-Cooperative Game Theory What is a game? Introduction A game is a decision problem in which there a multiple decision makers, each with pay-off interdependence Each decisions

More information

Machine Learning in Iterated Prisoner s Dilemma using Evolutionary Algorithms

Machine Learning in Iterated Prisoner s Dilemma using Evolutionary Algorithms ITERATED PRISONER S DILEMMA 1 Machine Learning in Iterated Prisoner s Dilemma using Evolutionary Algorithms Department of Computer Science and Engineering. ITERATED PRISONER S DILEMMA 2 OUTLINE: 1. Description

More information

Multiple Agents. Why can t we all just get along? (Rodney King)

Multiple Agents. Why can t we all just get along? (Rodney King) Multiple Agents Why can t we all just get along? (Rodney King) Nash Equilibriums........................................ 25 Multiple Nash Equilibriums................................. 26 Prisoners Dilemma.......................................

More information

Lecture #3: Networks. Kyumars Sheykh Esmaili

Lecture #3: Networks. Kyumars Sheykh Esmaili Lecture #3: Game Theory and Social Networks Kyumars Sheykh Esmaili Outline Games Modeling Network Traffic Using Game Theory Games Exam or Presentation Game You need to choose between exam or presentation:

More information

ECO 5341 Strategic Behavior Lecture Notes 3

ECO 5341 Strategic Behavior Lecture Notes 3 ECO 5341 Strategic Behavior Lecture Notes 3 Saltuk Ozerturk SMU Spring 2016 (SMU) Lecture Notes 3 Spring 2016 1 / 20 Lecture Outline Review: Dominance and Iterated Elimination of Strictly Dominated Strategies

More information

A Game Playing System for Use in Computer Science Education

A Game Playing System for Use in Computer Science Education A Game Playing System for Use in Computer Science Education James MacGlashan University of Maryland, Baltimore County 1000 Hilltop Circle Baltimore, MD jmac1@umbc.edu Don Miner University of Maryland,

More information

Game Theory. Vincent Kubala

Game Theory. Vincent Kubala Game Theory Vincent Kubala Goals Define game Link games to AI Introduce basic terminology of game theory Overall: give you a new way to think about some problems What Is Game Theory? Field of work involving

More information

17.5 DECISIONS WITH MULTIPLE AGENTS: GAME THEORY

17.5 DECISIONS WITH MULTIPLE AGENTS: GAME THEORY 666 Chapter 17. Making Complex Decisions plans generated by value iteration.) For problems in which the discount factor γ is not too close to 1, a shallow search is often good enough to give near-optimal

More information

CS 1571 Introduction to AI Lecture 12. Adversarial search. CS 1571 Intro to AI. Announcements

CS 1571 Introduction to AI Lecture 12. Adversarial search. CS 1571 Intro to AI. Announcements CS 171 Introduction to AI Lecture 1 Adversarial search Milos Hauskrecht milos@cs.pitt.edu 39 Sennott Square Announcements Homework assignment is out Programming and experiments Simulated annealing + Genetic

More information

Reinforcement Learning in Games Autonomous Learning Systems Seminar

Reinforcement Learning in Games Autonomous Learning Systems Seminar Reinforcement Learning in Games Autonomous Learning Systems Seminar Matthias Zöllner Intelligent Autonomous Systems TU-Darmstadt zoellner@rbg.informatik.tu-darmstadt.de Betreuer: Gerhard Neumann Abstract

More information

INTRODUCTION TO GAME THEORY

INTRODUCTION TO GAME THEORY 1 / 45 INTRODUCTION TO GAME THEORY Heinrich H. Nax hnax@ethz.ch & Bary S. R. Pradelski bpradelski@ethz.ch February 20, 2017: Lecture 1 2 / 45 A game Rules: 1 Players: All of you: https://scienceexperiment.online/beautygame/vote

More information

CSC304 Lecture 2. Game Theory (Basic Concepts) CSC304 - Nisarg Shah 1

CSC304 Lecture 2. Game Theory (Basic Concepts) CSC304 - Nisarg Shah 1 CSC304 Lecture 2 Game Theory (Basic Concepts) CSC304 - Nisarg Shah 1 Game Theory How do rational, self-interested agents act? Each agent has a set of possible actions Rules of the game: Rewards for the

More information

EconS Game Theory - Part 1

EconS Game Theory - Part 1 EconS 305 - Game Theory - Part 1 Eric Dunaway Washington State University eric.dunaway@wsu.edu November 8, 2015 Eric Dunaway (WSU) EconS 305 - Lecture 28 November 8, 2015 1 / 60 Introduction Today, we

More information

Introduction to Spring 2009 Artificial Intelligence Final Exam

Introduction to Spring 2009 Artificial Intelligence Final Exam CS 188 Introduction to Spring 2009 Artificial Intelligence Final Exam INSTRUCTIONS You have 3 hours. The exam is closed book, closed notes except a two-page crib sheet, double-sided. Please use non-programmable

More information

Game Theory. Vincent Kubala

Game Theory. Vincent Kubala Game Theory Vincent Kubala vkubala@cs.brown.edu Goals efine game Link games to AI Introduce basic terminology of game theory Overall: give you a new way to think about some problems What Is Game Theory?

More information

Game theory Computational Models of Cognition

Game theory Computational Models of Cognition Game theory Taxonomy Rational behavior Definitions Common games Nash equilibria Mixed strategies Properties of Nash equilibria What do NE mean? Mutually Assured Destruction 6 rik@cogsci.ucsd.edu Taxonomy

More information

Game Theory. Share information. Evaluate information (obtained from friends, acquaintances and coworkers) Develop trust. Accept or reject friendship

Game Theory. Share information. Evaluate information (obtained from friends, acquaintances and coworkers) Develop trust. Accept or reject friendship Æ ÇÌ Ë º ÅÁËÀÊ ÈÊÁÄ ¾ ¾¼½¾ Game Theory A social network is not a static structure the individuals in a social network must constantly interact in order to create social capital that reflects how a group

More information

SF2972: Game theory. Mark Voorneveld, February 2, 2015

SF2972: Game theory. Mark Voorneveld, February 2, 2015 SF2972: Game theory Mark Voorneveld, mark.voorneveld@hhs.se February 2, 2015 Topic: extensive form games. Purpose: explicitly model situations in which players move sequentially; formulate appropriate

More information

THEORY: NASH EQUILIBRIUM

THEORY: NASH EQUILIBRIUM THEORY: NASH EQUILIBRIUM 1 The Story Prisoner s Dilemma Two prisoners held in separate rooms. Authorities offer a reduced sentence to each prisoner if he rats out his friend. If a prisoner is ratted out

More information

Introduction to Game Theory

Introduction to Game Theory Introduction to Game Theory Lecture 2 Lorenzo Rocco Galilean School - Università di Padova March 2017 Rocco (Padova) Game Theory March 2017 1 / 46 Games in Extensive Form The most accurate description

More information

ECON 301: Game Theory 1. Intermediate Microeconomics II, ECON 301. Game Theory: An Introduction & Some Applications

ECON 301: Game Theory 1. Intermediate Microeconomics II, ECON 301. Game Theory: An Introduction & Some Applications ECON 301: Game Theory 1 Intermediate Microeconomics II, ECON 301 Game Theory: An Introduction & Some Applications You have been introduced briefly regarding how firms within an Oligopoly interacts strategically

More information

Chapter 2 Basics of Game Theory

Chapter 2 Basics of Game Theory Chapter 2 Basics of Game Theory Abstract This chapter provides a brief overview of basic concepts in game theory. These include game formulations and classifications, games in extensive vs. in normal form,

More information

Multiagent Systems: Intro to Game Theory. CS 486/686: Introduction to Artificial Intelligence

Multiagent Systems: Intro to Game Theory. CS 486/686: Introduction to Artificial Intelligence Multiagent Systems: Intro to Game Theory CS 486/686: Introduction to Artificial Intelligence 1 Introduction So far almost everything we have looked at has been in a single-agent setting Today - Multiagent

More information

What is... Game Theory? By Megan Fava

What is... Game Theory? By Megan Fava ABSTRACT What is... Game Theory? By Megan Fava Game theory is a branch of mathematics used primarily in economics, political science, and psychology. This talk will define what a game is and discuss a

More information

Non-Cooperative Game Theory

Non-Cooperative Game Theory Notes on Microeconomic Theory IV 3º - LE-: 008-009 Iñaki Aguirre epartamento de Fundamentos del Análisis Económico I Universidad del País Vasco An introduction to. Introduction.. asic notions.. Extensive

More information

Introduction to Game Theory

Introduction to Game Theory Introduction to Game Theory Managing with Game Theory Hongying FEI Feihy@i.shu.edu.cn Poker Game ( 2 players) Each player is dealt randomly 3 cards Both of them order their cards as they want Cards at

More information

Backward Induction and Stackelberg Competition

Backward Induction and Stackelberg Competition Backward Induction and Stackelberg Competition Economics 302 - Microeconomic Theory II: Strategic Behavior Shih En Lu Simon Fraser University (with thanks to Anke Kessler) ECON 302 (SFU) Backward Induction

More information