player 1 x>y>z x>z>y y>x>z y>z>x z>y>x z>x>y not aggressive aggressive most aggressive

Similar documents
Distributed Optimization and Games

Distributed Optimization and Games

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

Game theory Computational Models of Cognition

ECO 463. SimultaneousGames

Game Theory: Introduction. Game Theory. Game Theory: Applications. Game Theory: Overview

Prisoner 2 Confess Remain Silent Confess (-5, -5) (0, -20) Remain Silent (-20, 0) (-1, -1)

Multi-player, non-zero-sum games

Topics in Applied Mathematics

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

Finance Solutions to Problem Set #8: Introduction to Game Theory

Instability of Scoring Heuristic In games with value exchange, the heuristics are very bumpy Make smoothing assumptions search for "quiesence"

ECON 282 Final Practice Problems

CSE468 Information Conflict

Game Theory: introduction and applications to computer networks

INTRODUCTION TO GAME THEORY

(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

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

Math 464: Linear Optimization and Game

Microeconomics of Banking: Lecture 4

Chapter 15: Game Theory: The Mathematics of Competition Lesson Plan

Game Theory Refresher. Muriel Niederle. February 3, A set of players (here for simplicity only 2 players, all generalized to N players).

Lecture #3: Networks. Kyumars Sheykh Esmaili

Computational Methods for Non-Cooperative Game Theory

Terry College of Business - ECON 7950

Exercises for Introduction to Game Theory SOLUTIONS

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

Lecture 13(ii) Announcements. Lecture on Game Theory. None. 1. The Simple Version of the Battle of the Sexes

Games. Episode 6 Part III: Dynamics. Baochun Li Professor Department of Electrical and Computer Engineering University of Toronto

Game Theory Lecturer: Ji Liu Thanks for Jerry Zhu's slides

Student Name. Student ID

Mixed Strategies; Maxmin

Applied Game Theory And Strategic Behavior Chapter 1 and Chapter 2 review

Aspects of Game Theory & John Nash

LECTURE 26: GAME THEORY 1

Advanced Microeconomics (Economics 104) Spring 2011 Strategic games I

Game Theory. 4: Nash equilibrium in different games and mixed strategies

Applied Game Theory And Strategic Behavior Chapter 1 and Chapter 2. Author: Siim Adamson TTÜ 2010

Session Outline. Application of Game Theory in Economics. Prof. Trupti Mishra, School of Management, IIT Bombay

Copyright 2008, Yan Chen

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

Name. Midterm, Econ 171, February 27, 2014

Contents. MA 327/ECO 327 Introduction to Game Theory Fall 2017 Notes. 1 Wednesday, August Friday, August Monday, August 28 6

CMU-Q Lecture 20:

THEORY: NASH EQUILIBRIUM

NORMAL FORM (SIMULTANEOUS MOVE) GAMES

Computing Nash Equilibrium; Maxmin

Game Theory. 4: Nash equilibrium in different games and mixed strategies

Simultaneous-Move Games: Mixed Strategies. Games Of Strategy Chapter 7 Dixit, Skeath, and Reiley

INSTRUCTIONS: all the calculations on the separate piece of paper which you do not hand in. GOOD LUCK!

Lecture 6: Basics of Game Theory

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

Evolutionary Game Theory and Linguistics

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

Genetic Algorithms in MATLAB A Selection of Classic Repeated Games from Chicken to the Battle of the Sexes

Some introductory notes on game theory

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

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

W-S model prediction, Game theory. CS 249B: Science of Networks Week 06: Monday, 03/03/08 Daniel Bilar Wellesley College Spring 2008

Introduction to Game Theory

A Brief Introduction to Game Theory

Lect 15:Game Theory: the math of competition

Advanced Microeconomics: Game Theory

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

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

Part I. First Notions

Chapter 2 Basics of Game Theory

Spring 2014 Quiz: 10 points Answer Key 2/19/14 Time Limit: 53 Minutes (FAS students: Teaching Assistant. Total Point Value: 10 points.

Lecture 7: Dominance Concepts

DECISION MAKING GAME THEORY

Normal Form Games: A Brief Introduction

Weeks 3-4: Intro to Game Theory

GAME THEORY: STRATEGY AND EQUILIBRIUM

PARALLEL NASH EQUILIBRIA IN BIMATRIX GAMES ISAAC ELBAZ CSE633 FALL 2012 INSTRUCTOR: DR. RUSS MILLER

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

Summary Overview of Topics in Econ 30200b: Decision theory: strong and weak domination by randomized strategies, domination theorem, expected utility

Lecture 5: Subgame Perfect Equilibrium. November 1, 2006

Games of Perfect Information and Backward Induction

CS510 \ Lecture Ariel Stolerman

final examination on May 31 Topics from the latter part of the course (covered in homework assignments 4-7) include:

Nash Equilibrium. An obvious way to play? Player 1. Player 2. Player 2

1. Introduction to Game Theory

Introduction to Auction Theory: Or How it Sometimes

Minmax and Dominance

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

Computing optimal strategy for finite two-player games. Simon Taylor

14.12 Game Theory Lecture Notes Lectures 10-11

ECO 199 B GAMES OF STRATEGY Spring Term 2004 B February 24 SEQUENTIAL AND SIMULTANEOUS GAMES. Representation Tree Matrix Equilibrium concept

0.1 Battle of the Sexes. 0.2 Chicken. 0.3 Coordination Game

Grade 7/8 Math Circles. February 14 th /15 th. Game Theory. If they both confess, they will both serve 5 hours of detention.

2. The Extensive Form of a Game

Basics of Game Theory

Sequential Games When there is a sufficient lag between strategy choices our previous assumption of simultaneous moves may not be realistic. In these

Bonus Maths 5: GTO, Multiplayer Games and the Three Player [0,1] Game

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.

Terry College of Business - ECON 7950

Lecture 23. Offense vs. Defense & Dynamic Games

GAME THEORY MODULE 4. After completing this supplement, students will be able to: 1. Understand the principles of zero-sum, two-person games.

Chapter 3 Learning in Two-Player Matrix Games

Game Theory applied. A Tutorial

Transcription:

Sheets 14 Hawks and oves in a hicken Game The ordering of orderings Figure The Persuader Player 1 Persuader x Player 2 Opponent y z Figure 1 Ordering of orderings of the Persuader strategy strategy player 1 x>y>z x>z>y y>x>z y>z>x z>y>x z>x>y not aggressive aggressive most aggressive 1

Figure The Opponent Player 1 Persuader x Player 2 Opponent y z Figure 2 Ordering of orderings of the Opponent strategy strategy player 2 x>y>z y>x>z y>z>x x>z>y z>x>y z>y>x not aggressive most aggressive 2

Figure 3 Strategy : air strike Player 1 Persuader x Player 2 Opponent y player 2: z > y z 3

Figure 4 Strategy : invasion Player 1 Persuader x Player 2 Opponent y player 2: z > y z 4

Figure 5 Strategy : blockade Player 1 Persuader x Player 2 Opponent y player 2: y > z z 5

Figure 6 Soviets Player 1 Persuader x (, 3) Player 2 Opponent y (, 2) z (, 1) 6

Figure 7 Hawks & Soviets Player 1 Persuader x (1, 3) Player 2 Opponent y (2, 2) z (3, 1) 7

Figure 8 oves & Soviets Player 1 Persuader x (2, 3) Player 2 Opponent y (3, 2) z (1, 1) 8

From a formal point of view it does not matter whether the preferences of the US are z > y > x (Figure 7) or y > x > z (Figure 8). If the second player for whatever reason prefers outcome y to outcome z, then the outcome will be y in both cases. The success (outcome y) or failure (outcome z) is a decision that depends only on the choice of the second player. 9

The choice of a blockade is what Schelling calls a low-level intrusion which gives the opponent time to think about how to react (Schelling 1966: 77). Thus, the revealed preference gives us information about the underlying preferences of some action. Figure 9 The level of intrusion strategy strategy strategy instrument blockade air strike ordering x>y>z x>z>y y>x>z y>z>x z>y>x z>x>y disposition not aggressive aggressive most aggressive 10

The method of lottery ticket [1] A = p* + 1-p * B This result would be consistent with the payoffs we have attached: 2 utilities to outcome A, 3 utilities to outcome and 1 utility to outcome B: [2] 2 =.5 * 3 +.5 * 1 11

Figure 9 The lottery ticket method: p = ½ Player 1 x = 2 sure thing Player 2 y = 3 z = 1 probability p=½ probability 1-p 12

Figure 10 The lottery ticket method: p = 1 / 5 Player 1 x = 2 sure thing Player 2 y = 6 z = 1 probability p= 1 / 5 probability 1-p Another individual can have a different personal standard, for example, with p = 1 / 5. With the same equation, we can establish that the numerical values are x = 3, y = 6, and z = 1: Figure 10. [3] x = p* y + 1-p * z 13

Figure 11 The lottery ticket method: p = 4 / 5 Player 1 x = 2 sure thing Player 2 y = 2.2 z = 1 probability p= 4 / 5 probability 1-p [4] x = p* y + 1-p * z A third individual could be indifferent when p = 0.8. His payoffs would be x = 3, y = 2.2 and z = 1: 14

Von Neumann and Morgenstern already established that it makes no sense to use the method of the lottery ticket if the sure thing outcome is the highest preferred or the lowest preferred alternative. We expect the individual under consideration to possess a clear intuition whether he prefers the event A to the 50-50 combination of B or, or conversely. It is clear that if he prefers A to B and also to, then he will prefer it to the above combination as well; similarly, if he prefers B as well as to A, then he will prefer the combination too. But if he should prefer A to, say B, but at the same time to A, then any assertion about his preference of A against the combination contains fundamentally new information (Von Neumann and Morgenstern 2004: 18). With the lottery tickets, we can measure the numerical values of the orderings y > x > z and z > x > y, but not of the orderings y > z > x and z > y > x. 15

Figure 12 p = ½ Figure 13 p = 4 / 5 Figure 14 p = 1 / 5 16

Hawks and oves British evolutionary biologist John Maynard Smith in his Evolution and the Theory of Games (1982). The names hawk and dove represent two different strategies in a model of conflict over resources. Strategy Hawk stands for fighting for resources, while strategy ove is just posing a threatening stance without engaging in a fight. Figure 15 Hawk versus ove game ove () player 2 Hawk () player 1 ove () (15, 15) (0, 50) Hawk () (50, 0) (-25, -25) [6] 15 * (1-p) + 0 * p = 50 * (1-p) -25 + 50 * (p) 15 15p = 50 75p 60p = 35 p = 7 / 12 and thus (1-p) = 5 / 12 [7] 5 / 12 * 15 + 7 / 12 * 0 = 6,25 And the expected payoff for strategy Hawk is: [8] 5 / 12 * 50 + 7 / 12 * -25 = 6,25 17

Figure 16 Mixed strategies of the Hawk versus ove game player 2 ove () * 5 / 12 Hawk () * 7 / 12 player 1 ove () * 5 / 12 (15, 15) (0, 50) Hawk () * 7 / 12 (50, 0) (-25, -25) Figure 17 Payoff polygon of the Hawk versus ove Game (0, 50) H (15, 15) ESS (6 1 / 4, 6 1 / 4) Monopoly Pareto optimal solution (50, 0) H (-25, -25) HH ournot Equilibrium 18

The evolutionary theory of conflict The original evolutionary game is about animals contesting limited resources such as a favourable habitat. Maynard Smith describes two habitats, a favourable habitat in which an animal produces a relatively high number of offspring and a less favourable habitat in which an animal produces a low number of offspring on average. The contest over the habitat has the value V, i.e. the gain in fitness due to a more favourable habitat. Fighting over the habitat can lead to injury and the cost of the injury is, which stands for the loss in fitness. The strategy in the games of evolutionary biology does not refer to two different animals, a dove and a hawk, but to two different kinds of behaviour of the same animal. Strategy ove stands for ooperate and Hawk for efect. If two hawks fight, then each hawk has a 50% chance to gain V or lose, and the expected payoff is ½(V-). A hawk will win value V in the confrontation with a dove, and the dove gets nothing. Two doves will split the gain of sharing the favourable habitat V/2. Figure 18 illustrates the payoff matrix of the Hawk-ove game that represents the fitness for the players (Maynard Smith 1982: 12). 19

If the value of the gain in fitness is high relative to the cost of being injured, say V = 6 and =2, then the game becomes a Prisoner s ilemma game (ixit and Skeath 2004: 448) Figure 18 Hawk versus ove game ove () player 2 Hawk () player 1 ove () V/2, V/2 0, V Hawk () V, 0 ½ (V-), ½ (V-) Figure 19 Game with V = 6 and = 2: Prisoner s ilemma ove () player 2 Hawk () player 1 ove () 3, 3 0, 6 Hawk () 6, 0 2, 2 20

Figure 20 Prisoner s ilemma game player 2 ooperate () efect () player 1 ooperate () 3, 3 1, 4 efect () 4, 1 2, 2 21

On the other hand, if the cost of being injured is high and the gain in fitness is low, say V = 2 and = 4, then the game is a hicken Game (ixit and Skeath 2004: 448) with outcomes H and H as Nash equilibria. Figure 21 Game with V = 2 and = 4: hicken Game ove () player 2 Hawk () player 1 ove () 1, 1 0, 2 Hawk () 2, 0-1, -1 Figure 22 hicken Game swerve () player 2 drive straight () player 1 swerve () (3, 3) (2, 4) drive straight () (4, 2) (1, 1) 22

Figure 23 Payoff polygon of the hicken Game (2, 4) H mixed Nash equilibrium (3, 3) (2½, 2½) (4, 2) H (1, 1) HH 23