MiniMax Principle in Game Theory Slides Made by Senjuti Basu Roy.

Slides:



Advertisements
Similar presentations
Thursday, March 7 Duality 2 – The dual problem, in general – illustrating duality with 2-person 0-sum game theory Handouts: Lecture Notes.
Advertisements

Chapter 17: Making Complex Decisions April 1, 2004.
Oct 9, 2014 Lirong Xia Hypothesis testing and statistical decision theory.
9.1 Strictly Determined Games Game theory is a relatively new branch of mathematics designed to help people who are in conflict situations determine the.
GAME THEORY.
Nash’s Theorem Theorem (Nash, 1951): Every finite game (finite number of players, finite number of pure strategies) has at least one mixed-strategy Nash.
Module 4 Game Theory To accompany Quantitative Analysis for Management, Tenth Edition, by Render, Stair, and Hanna Power Point slides created by Jeff Heyl.
Mechanism Design without Money Lecture 1 Avinatan Hassidim.
Statistics and Probability
Strongly based on Slides by Vincent Conitzer of Duke
Totally Unimodular Matrices
Mixed Strategies CMPT 882 Computational Game Theory Simon Fraser University Spring 2010 Instructor: Oliver Schulte.
Lecturer: Moni Naor Algorithmic Game Theory Uri Feige Robi Krauthgamer Moni Naor Lecture 8: Regret Minimization.
C&O 355 Mathematical Programming Fall 2010 Lecture 12 N. Harvey TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AA A.
A Beautiful Game John C. Sparks AFRL/WS (937) Wright-Patterson Educational Outreach The Air Force Research Laboratory.
Introduction to Game theory Presented by: George Fortetsanakis.
A very little Game Theory Math 20 Linear Algebra and Multivariable Calculus October 13, 2004.
Simultaneous- Move Games with Mixed Strategies Zero-sum Games.
Decision Theory.
Operations Research Assistant Professor Dr. Sana’a Wafa Al-Sayegh 2 nd Semester ITGD4207 University of Palestine.
MIT and James Orlin © Game Theory 2-person 0-sum (or constant sum) game theory 2-person game theory (e.g., prisoner’s dilemma)
Copyright (c) 2003 Brooks/Cole, a division of Thomson Learning, Inc
Study Group Randomized Algorithms 21 st June 03. Topics Covered Game Tree Evaluation –its expected run time is better than the worst- case complexity.
Game theory.
Shengyu Zhang The Chinese University of Hong Kong.
Peter Lam Discrete Math CS. Outline  Use game theory to solve strictly determining games  Non strictly games  Create models for games  Find optimal.
1 1 Slide Decision Analysis n Structuring the Decision Problem n Decision Making Without Probabilities n Decision Making with Probabilities n Expected.
1 1 Slide Decision Analysis Professor Ahmadi. 2 2 Slide Decision Analysis Chapter Outline n Structuring the Decision Problem n Decision Making Without.
Part 3: The Minimax Theorem
Duality Lecture 10: Feb 9. Min-Max theorems In bipartite graph, Maximum matching = Minimum Vertex Cover In every graph, Maximum Flow = Minimum Cut Both.
Artificial Intelligence for Games and Puzzles1 Games in the real world Many real-world situations and problems.
Decision Making Under Uncertainty Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.
UNIT II: The Basic Theory Zero-sum Games Nonzero-sum Games Nash Equilibrium: Properties and Problems Bargaining Games Bargaining and Negotiation Review.
Games of Chance Introduction to Artificial Intelligence COS302 Michael L. Littman Fall 2001.
Artificial Intelligence for Games and Puzzles1 Games in the real world Many real-world situations and.
Game Theory and Risk Analysis for Counterterrorism
UNIT II: The Basic Theory Zero-sum Games Nonzero-sum Games Nash Equilibrium: Properties and Problems Bargaining Games Bargaining and Negotiation Review.
Game Theory Statistics 802. Lecture Agenda Overview of games 2 player games representations 2 player zero-sum games Render/Stair/Hanna text CD QM for.
Experts Learning and The Minimax Theorem for Zero-Sum Games Maria Florina Balcan December 8th 2011.
Game Theory.
1 Introduction to Randomized Algorithms Srikrishnan Divakaran DA-IICT.
1 Introduction to Randomized Algorithms Srikrishnan Divakaran DA-IICT.
The Multiplicative Weights Update Method Based on Arora, Hazan & Kale (2005) Mashor Housh Oded Cats Advanced simulation methods Prof. Rubinstein.
Standard and Extended Form Games A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor, SIUC.
1 1 Slide Decision Theory Professor Ahmadi. 2 2 Slide Learning Objectives n Structuring the decision problem and decision trees n Types of decision making.
Chapter 14 Game Theory to accompany Operations Research: Applications and Algorithms 4th edition by Wayne L. Winston Copyright (c) 2004 Brooks/Cole, a.
1 CRP 834: Decision Analysis Week Four Notes. 2 Review Game Theory –Classification and Description –Two Person Zero-Sum Game Game w/ Dominating Strategy.
Chapter 11 Game Theory Math Game Theory What is it? – a way to model conflict and competition – one or more "players" make simultaneous decisions.
Games. Adversaries Consider the process of reasoning when an adversary is trying to defeat our efforts In game playing situations one searches down the.
Game Theory, Part 2 Consider again the game that Sol and Tina were playing, but with a different payoff matrix: H T Tina H T Sol.
Part 3 Linear Programming
Models for Strategic Marketing Decision Making. Market Entry Decisions To enter first or to wait Sources of First-Mover Advantages –Technological leadership.
Mixed Strategies and Repeated Games
1 What is Game Theory About? r Analysis of situations where conflict of interests is present r Goal is to prescribe how conflicts can be resolved 2 2 r.
1. 2 You should know by now… u The security level of a strategy for a player is the minimum payoff regardless of what strategy his opponent uses. u A.
1 a1a1 A1A1 a2a2 a3a3 A2A Mixed Strategies When there is no saddle point: We’ll think of playing the game repeatedly. We continue to assume that.
Zero-sum Games The Essentials of a Game Extensive Game Matrix Game Dominant Strategies Prudent Strategies Solving the Zero-sum Game The Minimax Theorem.
Statistics Overview of games 2 player games representations 2 player zero-sum games Render/Stair/Hanna text CD QM for Windows software Modeling.
INDEX Introduction of game theory Introduction of game theory Significance of game theory Significance of game theory Essential features of game theory.
Introduction to Game Theory Presented by 蘇柏穎 2004/12/9 2004/12/9.
GAME THEORY Day 5. Minimax and Maximin Step 1. Write down the minimum entry in each row. Which one is the largest? Maximin Step 2. Write down the maximum.
By: Donté Howell Game Theory in Sports. What is Game Theory? It is a tool used to analyze strategic behavior and trying to maximize his/her payoff of.
Game Algorithms Prepared for COSC 6111 By Stephanie Wilson November 15th, 2006.
Hypothesis testing and statistical decision theory
Game Theory Just last week:
Input – Output Models P = # of items produced
Chapter 6 Game Theory (Module 4) 1.
Lecture 20 Linear Program Duality
Operations Research: Applications and Algorithms
MinMax Principle in Game Theory – continued….
Presentation transcript:

MiniMax Principle in Game Theory Slides Made by Senjuti Basu Roy

 MiniMax Principle from Game Theory is used to provide a lower bound of the running time of the Randomized AND-OR tree algorithm.  Rachael and Chris play a game with three objects:  Stone  Paper  Scissors  In this simultaneous game,both Rachael and Chris pick up one of these three objects.  This three objects have the following order of preference : Stone >> (preferred than) Scissors Scissors >> Paper and Paper >> Stone. The winner of the game Played by Rachael and Chris is determined by the following way: The person who picks up a more preferred item than the other is the winner. The loser pays $1 to the winner and the outcome is a draw when both of them picks up the same object

Scissors Stone Paper Stone Matrix for Scissors-Paper-Stone This is called Two Person Zero Sum Game since Money are Getting exchanged Between hands and There is no External money flow.

A Deterministic Strategy – Chris Pays Rachael Scissors Stone Paper Stone Scissors The minimum Amount Rachael Makes if she selects Paper Stone Maxm Amount Chris has To pay Rachael if he selects ScissorsPaperStone

Another Pay Off Matrix Scissors Stone Scissors Paper V R = max i {min j M ij } V C = min j {max i M ij } V R = 0 V C = 0

What is V R and V c in a Conservative Game Strategy? V R = The lower bound of the amount of money that Rachael can make/round V c = The upper bound of the money that Chris can give to Rachael. And in general V R <= V c For certain Pay-off matrices, V R = V c

Probabilistic Game Playing Strategy 1 2 n 12n n x n PDF of Rachael’s moves PDF of Chris’ moves Expected [payoff] = (Σ i=1..n) (Σ j=1..n) p i M ij q j = p T Mq

How does this strategy work? - Von Neumann’s MiniMax Principle  Say Rachael has selected p. Then Chris should select a distribution q such that P T Mq is minimized.  Min q P T Mq.  Rachael wants V R = max p min q P T Mq.  Chris wants V C = min q max p P T Mq.  In the probabilistic game playing strategy, V R = V C  This is known as Von Neumann’s MiniMax Principle.

PDF interpretation of Deterministic Game:  All moves get 0 as the probability and the move chosen by the player gets 1.  PDF looks like Loomi’s Theorem: It says max p min e P T M e = min q max f f T M q, where e and f are special distributions has only 1 and 0 everywhere else.