ECE 586GT: Problem Set 1: Problems and Solutions Analysis of static games

Similar documents
ECE 586BH: Problem Set 5: Problems and Solutions Multistage games, including repeated games, with observed moves

6.254 : Game Theory with Engineering Applications Lecture 3: Strategic Form Games - Solution Concepts

Solution to Tutorial 1

Solution to Tutorial /2013 Semester I MA4264 Game Theory

Chapter 10: Mixed strategies Nash equilibria, reaction curves and the equality of payoffs theorem

Introduction to Multi-Agent Programming

Regret Minimization and Security Strategies

Game theory and applications: Lecture 1

PAULI MURTO, ANDREY ZHUKOV

The Ohio State University Department of Economics Second Midterm Examination Answers

CSI 445/660 Part 9 (Introduction to Game Theory)

Rationalizable Strategies

PAULI MURTO, ANDREY ZHUKOV. If any mistakes or typos are spotted, kindly communicate them to

Game Theory Problem Set 4 Solutions

On Existence of Equilibria. Bayesian Allocation-Mechanisms

SI 563 Homework 3 Oct 5, Determine the set of rationalizable strategies for each of the following games. a) X Y X Y Z

MATH 4321 Game Theory Solution to Homework Two

CS711: Introduction to Game Theory and Mechanism Design

FDPE Microeconomics 3 Spring 2017 Pauli Murto TA: Tsz-Ning Wong (These solution hints are based on Julia Salmi s solution hints for Spring 2015.

FDPE Microeconomics 3 Spring 2017 Pauli Murto TA: Tsz-Ning Wong (These solution hints are based on Julia Salmi s solution hints for Spring 2015.

Problem Set 2 - SOLUTIONS

Best-Reply Sets. Jonathan Weinstein Washington University in St. Louis. This version: May 2015

Complexity of Iterated Dominance and a New Definition of Eliminability

Math 167: Mathematical Game Theory Instructor: Alpár R. Mészáros

10.1 Elimination of strictly dominated strategies

6.207/14.15: Networks Lecture 9: Introduction to Game Theory 1

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

Game Theory: Normal Form Games

1 x i c i if x 1 +x 2 > 0 u i (x 1,x 2 ) = 0 if x 1 +x 2 = 0

1 R. 2 l r 1 1 l2 r 2

Game Theory. VK Room: M1.30 Last updated: October 22, 2012.

Bayesian Nash Equilibrium

6.207/14.15: Networks Lecture 10: Introduction to Game Theory 2

Discrete Mathematics for CS Spring 2008 David Wagner Final Exam

Microeconomic Theory August 2013 Applied Economics. Ph.D. PRELIMINARY EXAMINATION MICROECONOMIC THEORY. Applied Economics Graduate Program

Using the Maximin Principle

Ph.D. Preliminary Examination MICROECONOMIC THEORY Applied Economics Graduate Program June 2017

Introduction to Industrial Organization Professor: Caixia Shen Fall 2014 Lecture Note 5 Games and Strategy (Ch. 4)

Equilibrium payoffs in finite games

Name. Answers Discussion Final Exam, Econ 171, March, 2012

Microeconomics II. CIDE, MsC Economics. List of Problems

MA300.2 Game Theory 2005, LSE

Strategy -1- Strategy

Introduction. Microeconomics II. Dominant Strategies. Definition (Dominant Strategies)

Expectations & Randomization Normal Form Games Dominance Iterated Dominance. Normal Form Games & Dominance

Player 2 H T T -1,1 1, -1

CUR 412: Game Theory and its Applications, Lecture 4

Today. Applications of NE and SPNE Auctions English Auction Second-Price Sealed-Bid Auction First-Price Sealed-Bid Auction

6.207/14.15: Networks Lecture 9: Introduction to Game Theory 1

MAT 4250: Lecture 1 Eric Chung

Outline for today. Stat155 Game Theory Lecture 13: General-Sum Games. General-sum games. General-sum games. Dominated pure strategies

Solutions of Bimatrix Coalitional Games

CS711 Game Theory and Mechanism Design

MS&E 246: Lecture 2 The basics. Ramesh Johari January 16, 2007

Microeconomic Theory II Preliminary Examination Solutions Exam date: June 5, 2017

preferences of the individual players over these possible outcomes, typically measured by a utility or payoff function.

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

(a) Describe the game in plain english and find its equivalent strategic form.

Games of Incomplete Information

In reality; some cases of prisoner s dilemma end in cooperation. Game Theory Dr. F. Fatemi Page 219

Their opponent will play intelligently and wishes to maximize their own payoff.

Sequential-move games with Nature s moves.

Economics 703: Microeconomics II Modelling Strategic Behavior

Game Theory Lecture #16

Economics 109 Practice Problems 1, Vincent Crawford, Spring 2002

Outline Introduction Game Representations Reductions Solution Concepts. Game Theory. Enrico Franchi. May 19, 2010

Game Theory: Additional Exercises

Yao s Minimax Principle

Notes on Auctions. Theorem 1 In a second price sealed bid auction bidding your valuation is always a weakly dominant strategy.

In the Name of God. Sharif University of Technology. Microeconomics 2. Graduate School of Management and Economics. Dr. S.

1 Solutions to Homework 4

Mixed Strategies. In the previous chapters we restricted players to using pure strategies and we

CS 331: Artificial Intelligence Game Theory I. Prisoner s Dilemma

Advanced Microeconomic Theory EC104

Game Theory. Wolfgang Frimmel. Repeated Games

Problem 3 Solutions. l 3 r, 1

Introduction to Game Theory

CS364A: Algorithmic Game Theory Lecture #14: Robust Price-of-Anarchy Bounds in Smooth Games

Math 152: Applicable Mathematics and Computing

Microeconomics of Banking: Lecture 5

G5212: Game Theory. Mark Dean. Spring 2017

Test 1. ECON3161, Game Theory. Tuesday, September 25 th

Game Theory: Minimax, Maximin, and Iterated Removal Naima Hammoud

Outline for today. Stat155 Game Theory Lecture 19: Price of anarchy. Cooperative games. Price of anarchy. Price of anarchy

Preliminary Notions in Game Theory

Finding Mixed-strategy Nash Equilibria in 2 2 Games ÙÛ

m 11 m 12 Non-Zero Sum Games Matrix Form of Zero-Sum Games R&N Section 17.6

CMPSCI 240: Reasoning about Uncertainty

ECON 803: MICROECONOMIC THEORY II Arthur J. Robson Fall 2016 Assignment 9 (due in class on November 22)

Duopoly models Multistage games with observed actions Subgame perfect equilibrium Extensive form of a game Two-stage prisoner s dilemma

Midterm #2 EconS 527 [November 7 th, 2016]

Advanced Microeconomics

Radner Equilibrium: Definition and Equivalence with Arrow-Debreu Equilibrium

ECO 5341 (Section 2) Spring 2016 Midterm March 24th 2016 Total Points: 100

Microeconomics Comprehensive Exam

January 26,

Answer Key: Problem Set 4

Strategy -1- Strategic equilibrium in auctions

Ph.D. Preliminary Examination MICROECONOMIC THEORY Applied Economics Graduate Program June 2015

Iterated Dominance and Nash Equilibrium

Transcription:

University of Illinois Fall 2018 ECE 586GT: Problem Set 1: Problems and Solutions Analysis of static games Due: Tuesday, Sept. 11, at beginning of class Reading: Course notes, Sections 1.1-1.4 1. [A random zero sum game] ( ) A B Consider a two-player zero-sum game corresponding to the matrix. The players C D select an element of the matrix in the following way: player 1 selects a row and player 2 selects a column. The selected element is the payoff of player 2 and the negative of the payoff of player 1. Thus, player 1 seeks to minimize the element selected and player 2 seeks to maximize it. Suppose that A, B, C, D are independent and identically distributed continuous-type random variables. Suppose both players know the values of the random variables before selecting their actions. (Hint: The event two or more of the random variables are equal has probability zero, so assume without loss of generality that the random variables take different values. By symmetry, the probability any k of the random variables have a particular order is 1/k!. For example, P {A < B < C} = 1/6.) (a) Find the probability there is more than one pure-strategy Nash equilibrium (NE). Solution: There are four possible pure strategy profiles, which we refer to by their payoffs for player 2. Profile A is an NE if and only if B < A < C. So if A is an NE, neither B or C can be an NE. Similarly, D is an NE if and only if C > D > B. Since {B < C} {B > C} =, A and D cannot both be NEs. Thus, the probability there is more than one pure-strategy NE is zero. (b) Find the probability there is at least one pure-strategy NE. Solution: Profile A is an NE if and only if B < A < C, which has probability 1/6. By symmetry, any of the four profiles has probability 1/6 to be an NE, and the probability two or more of them are NEs is zero. Thus, the probability there is at least one NE is 4/6 = 2/3. (c) Find the probability player 1 has a dominant strategy. Solution: The first row is a dominant strategy if and only if {A < B} {C < D}, which has probability 1/4. Similarly, the second row is a dominant strategy with probability 1/4. Thus, the probability player 1 has a dominant strategy is 1/4+ 1/4, or 1/2. (d) Find the probability both players have a dominant strategy. Solution: If both players have a dominant strategy, then both players using their dominant strategy is a strategy profile. The event that strategy profile A represents a pair of dominant strategies is the event A < C, B < D, A > B, and C > D. In other words, it is the event that B is the smallest and C is the largest of the four random variables, or it is the union of the two events B < A < D < C and B < D < A < C, which has probability 2/4! = 1/12. Hence, the probability both players have a dominant strategy is 4/12 = 1/3. (Comparing to part (b), we can conclude that given there exists an NE, the conditional probability both players have dominant strategies is 1/2.)

2. [Territory control game on a graph] An application of the game in this problem could be for each of a set of players to decide where to place their fast food restaurant, under the assumption any customers will travel to the nearest fast food restaurant. Suppose n 2 and G = (V, E) is an undirected graph with vertex set V and edge set E. Consider the n player game such that the action of each player is to select a vertex in V. Two or more players can select the same vertex. Given the set of vertices selected by the players, each vertex v in the graph assigns total payoff one among the players, divided equally among those players who selected vertices the closest to the vertex v, where the distance between two vertices is the minimum number of edges in a path from one vertex to the other. For example, if there are no ties, the vertex v assigns payoff one to the player with selected vertex closest to v. The total payoff of a player is the sum over all vertices of the payoff assigned to that player. Thus, the sum of the payoffs of all players is V for any choices of the players. (a) Does there always exist at least one Nash equilibrium in mixed strategies? Solution: Yes, by Nash s theorem for finite games. (b) Consider the line graph G with V = {1, 2,..., 100} and E = {[i, i + 1] : 1 i 99}. Suppose there are two players (n = 2). Find the set of all pure strategy Nash equilibria. Solution: Suppose (s 1, s 2 ) is a NE. It is necessary that s 1 s 2 1, or else either player i could increase his/her payoff by moving s i closer to s i. Given that, it is also necessary that {s 1, s 2 } {50, 51}, or else one of the players i selecting an action furthest from {50, 51} could get a larger payoff by moving s i one step closer to {50, 51}. That leaves us with the following possible strategy profiles: (50,50), (50,51), (51,50), (51,51), and it is easily checked that all four of these strategy profiles are NE. (c) Is there a dominant strategy for a player in the game of part (b)? Solution: No. For example, if player 1 selects s 1 with s 1 49, the unique best response of player 2 is to select s 2 = s 1 + 1. Thus, there is no response for player 2 that is optimal for any choice made by player 1. (d) Repeat part (b) for three players, n = 3. Solution: We show by argument by contradiction that there is no NE in pure strategies for n = 3. For the sake of argument by contradiction, suppose (s 1, s 2, s 3 ) is a NE. Reorder the strategies if necessary so that s 1 s 2 s 3. It is necessary that s 2 s 1 1, or else player 1 could get a larger payoff by increasing s 1 by one. It is similarly necessary that s 3 s 2 1. It is impossible for s 1 = s 2 = s 3, because in that case any one player could increase his/her payoff from 100/3 to at least 50 by changing his/her action by one. It is also impossible for s 1, s 2, s 3 to be consecutive integers, because player 2 would be able to increase his/her payoff from 1 to at least 49. The remaining possibilities are when two of the actions are equal and the third is different by one. So consider the action profile (k, k, k + 1) for some integer k with 1 k 99. Cases k = 1 and k = 99 can be easily eliminated separately, so we can restrict attention to 2 k 98. The payoffs for the three players are k/2, k/2, 100 k respectively. If player 1 changed strategy to k + 2, his/her payoff would change to 100 k 1, so it must be that 100 k 1 k/2 or k 66. If player 3 changed strategy to k 1, his/her payoff would change to k 1, implying that k 1 100 k or 2k 101 or k 50. Thus, if order for (k, k, k + 1) to be an NE, it is necessary that k 66 and k 50, which is impossible. There are no remaining possibilities for (s 1, s 2, s 3 ) to be an NE; the proof by contradiction is complete. 2

3. [Possession is nine-tenths of the law] Consider { the normal form game G = (I, (S i ), (u i )) with I = {1,..., n} = [n], S i = [0, 1], and si if s u i (s i ) = 1 +... + s n 1. For example, suppose there is a pie, and every player 0 else declares what fraction of the pie he/she will take. Players get what they declare if the sum of the fractions is less than or equal to one. Else none get any pie. (a) Find all dominant strategies for a given player. Justify your answer. Solution: There are none. For a given player i and any x [0, 1], it is possible that the sum of the actions of other players is x. Then the unique best response of player i is s i = 1 x. Therefore, there is no single action of player i that is always a best response. (b) Find all Nash equilibria in pure strategies. (Include them all. Even ones such that all players get zero payoff.) Solution: Let s = (s 1,..., s n ) be a strategy profile. If i s i < 1 then s is not a NE, because any player could increase his/her payoff by unilaterally increasing his/her action by = 1 i s i. If i s i = 1 then s is a NE no player can unilaterally get a larger payoff. If i s i > 1 then s is a NE if and only if no player can select a different action to get a strictly positive payoff, with is equivalent to the condition s i 1 for all i, where s i denotes the sum of the actions of all players except for player i. 4. [Agreeing to disagree] Suppose n 3 and consider the normal form game with n players, I = [n], placed in a circle in order of index with wrap-around, so player n { is next to players n 1 and 1. Let S i = {0, 1}; 1 if si 1 = s each player i declares a bit s i. Let u i (s i ) = i+1 s i for i I, where, by 0 else notational convention, s 0 = s n and s n+1 = s 1. (a) Find a simple rule to determine whether a given strategy profile s = (s 1,..., s n ) is a Nash equilibrium. Justify your answer. Solution: A run for s is a set of consecutive indices (modulo n) such that the bits of s are identical.i We claim that s is a Nash equilibrium if an only if all runs have length one or two. If s is a Nash equilibrium it cannot have a run of length three or more, or else one of the players not at the endpoints of the run could increase his/her payoff by switching actions. If all runs have length one or two, then if a player is in a run of length one, it cannot increase his/her payoff by switching, because the payoff is already at the maximum, namely one. If the player is in a run of length 2, the payoff could not increase his/her payoff by switching actions such a switch would leave the payoff at zero. (b) Give an example of a Nash equilibrim in non-degenerate mixed strategies. Justify your answer. Solution: Let σ = (σ i ) i I where σ i = (0.5, 0.5) for each i. In other words, σ is the profile such that each player selects an action by a fair coin flip. We claim that σ is a NE. It is true because for other players using σ i, the expected payoff of player i is 1/4 for either action. So σ i is a best response to σ i for all i. 5. [True or false] Show the following statement is true, or show it is false. If a player in a normal form finite game has a dominant strategy, then the player must play that strategy with probability one for any correlated equilibrium. 3

Solution: True. Suppose p is a correlated equilibrium, which by definition means it is a probability distribution over the set of strategy profiles S = S 1... S n such that for every player i and every strategy s i for player i, p(s i, s i )(u i (s i, s i ) u i (s i, s i )) 0. (1) s i S i Suppose s i is a dominant strategy for some player i, so that u i(s i, s i ) u(s i, s i) < 0 for all s i with s i s i and any choice of s i. Then for any strategy s i for player i with s i s i, every term in the sum in (1) is less than or equal to zero, and is strictly less than zero if p(s i, s i ) > 0. Hence p(s i, s i ) = 0 for all s i. Thus, player i uses s i with probability zero for any s i s i. Since the game is finite, player i thus must use s i with probability one. 6. [Guessing 2/3 of the average] Consider the following game for n players. Each of the players selects a number from the set {1,..., 100}, and a cash prize is split evenly among the players who s numbers are closest to two-thirds the average of the n numbers chosen. (a) Show that the problem is solvable by iterated elimination of weakly dominated strategies, meaning the method can be used to eliminate all but one strategy for each player, which necessarily gives a Nash equilibrium. (A strategy µ i of a player i is called weakly dominated if there is another strategy µ i that always does at least as well as µ i, and is strictly better than µ i for some vector of strategies of the other players.) Solution: Any choice of number in the interval {68,..., 100} is weakly dominated, because replacing a choice in that interval by the choice 67 (here 67 is (2/3)100 rounded to the nearest integer) would not cause a winning player to lose, while, for some choices of the other players, it could cause a losing player to win. Thus, after one step of elimination, we assume all players select numbers in the interval {1,..., 67}. After two steps of elimination we assume players select numbers in the set {1,, 45}. After three steps, {1,, 30}, and so on. At each step the set of remaining strategies has the form {1,..., k}, and as long as k 2 the set shrinks at the next step. So the procedure terminates when all players choose the number one. (b) Give an example of a two player game, with two possible actions for each player, such that iterated elimination of weakly dominated strategies can eliminate a Nash equilibrium. (Hint: The eliminated Nash equilibrium might not be very good for either player.) ( ) 1 0 Solution: A bimatrix game with A 1 = A 2 = gives such an example. Playing 0 0 2 is weakly dominated for each player, and eliminating those choices leads to the Nash equilibrium (1, 1). However, (2, 2) is also a Nash equilibrium. (c) Show that the Nash equilibrium found in part (a) is the unique mixed strategy Nash equilibrium (as usual we consider pure strategies to be special cases of mixed strategies). (Hint: Let k be the largest integer such that there exists at least one player choosing k with strictly positive probability. Show that k = 1.) Solution: Consider a Nash equilibrium of mixed strategies. Let k be the largest integer such that there exists at least one player i choosing k with strictly positive probability. To complete the proof, we show that k = 1, meaning all players always choose the number one. For the sake of argument by contradiction, suppose k 2. Let player i denote a player that plays k with positive probability. For any choice of strategies of 4

other players, player i has a pure strategy with a strictly positive probability of winning. Since k must be a best response for player i, it must therefore also have a strictly positive probability of winning. It is impossible for player i to win if no other chosen numbers are equal to k. (Indeed, if player i were the only one to choose k, the second highest chosen number would be strictly closer to 2/3 of the average than k.) Thus, at least one of the other players must have a strictly positive probability of choosing k. But this means that player i could strictly increase her payoff by selecting k 1 instead of k (indeed, such change would never change her from winning to losing, and in case she wins, she would win strictly more with positive probability) which contradicts the requirement that k be a best response for player i. This completes the argument by contradiction. 5