The Monty Hall Problem
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Game Theory Lecture Notes
Game Theory: Penn State Math 486 Lecture Notes Version 2.1.1 Christopher Griffin « 2010-2021 Licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License With Major Contributions By: James Fan George Kesidis and Other Contributions By: Arlan Stutler Sarthak Shah Contents List of Figuresv Preface xi 1. Using These Notes xi 2. An Overview of Game Theory xi Chapter 1. Probability Theory and Games Against the House1 1. Probability1 2. Random Variables and Expected Values6 3. Conditional Probability8 4. The Monty Hall Problem 11 Chapter 2. Game Trees and Extensive Form 15 1. Graphs and Trees 15 2. Game Trees with Complete Information and No Chance 18 3. Game Trees with Incomplete Information 22 4. Games of Chance 24 5. Pay-off Functions and Equilibria 26 Chapter 3. Normal and Strategic Form Games and Matrices 37 1. Normal and Strategic Form 37 2. Strategic Form Games 38 3. Review of Basic Matrix Properties 40 4. Special Matrices and Vectors 42 5. Strategy Vectors and Matrix Games 43 Chapter 4. Saddle Points, Mixed Strategies and the Minimax Theorem 45 1. Saddle Points 45 2. Zero-Sum Games without Saddle Points 48 3. Mixed Strategies 50 4. Mixed Strategies in Matrix Games 53 5. Dominated Strategies and Nash Equilibria 54 6. The Minimax Theorem 59 7. Finding Nash Equilibria in Simple Games 64 8. A Note on Nash Equilibria in General 66 Chapter 5. An Introduction to Optimization and the Karush-Kuhn-Tucker Conditions 69 1. A General Maximization Formulation 70 2. Some Geometry for Optimization 72 3. -
Let's Make a Deal – the Monty Hall Problem
Simulation and Statistical Exploration of Data (Let’s Make a Deal – The Monty Hall Problem), using the new ClassPad300-technology Ludwig Paditz, University of Applied Sciences Dresden (FH), Germany Statement of the Problem The Monty Hall problem involves a classical game show situation and is named after Monty Hall*), the long-time host of the TV game show Let's Make a Deal. There are three doors labeled 1, 2, and 3. A car is behind one of the doors, while goats are behind the other two: The rules are as follows: 1. The player selects a door. 2. The host selects a different door and opens it. 3. The host gives the player the option of switching from the original choice to the remaining closed door. 4. The door finally selected by the player is opened and he either wins or loses. By the help of the ClassPad300 we will simulate N (say N=100) such game show situations to see, if the option of switching the door is a good or a bad option to improve the chance to win. The experiments help our students better to understand the randomness and the statistic methods of every day life. *) Monty Hall was born on August 25, 1924 in Canada. Hall attended the University of Manitoba, graduating in 1945, and served in the Canadian Army during World War II. He immigrated to the United States in 1955, and for the next few years worked in radio and television for the NBC and CBS networks. In 1963, Hall began as emcee for the game show Let's Make a Deal, the role that would make him famous. -
Frequently Asked Questions in Mathematics
Frequently Asked Questions in Mathematics The Sci.Math FAQ Team. Editor: Alex L´opez-Ortiz e-mail: [email protected] Contents 1 Introduction 4 1.1 Why a list of Frequently Asked Questions? . 4 1.2 Frequently Asked Questions in Mathematics? . 4 2 Fundamentals 5 2.1 Algebraic structures . 5 2.1.1 Monoids and Groups . 6 2.1.2 Rings . 7 2.1.3 Fields . 7 2.1.4 Ordering . 8 2.2 What are numbers? . 9 2.2.1 Introduction . 9 2.2.2 Construction of the Number System . 9 2.2.3 Construction of N ............................... 10 2.2.4 Construction of Z ................................ 10 2.2.5 Construction of Q ............................... 11 2.2.6 Construction of R ............................... 11 2.2.7 Construction of C ............................... 12 2.2.8 Rounding things up . 12 2.2.9 What’s next? . 12 3 Number Theory 14 3.1 Fermat’s Last Theorem . 14 3.1.1 History of Fermat’s Last Theorem . 14 3.1.2 What is the current status of FLT? . 14 3.1.3 Related Conjectures . 15 3.1.4 Did Fermat prove this theorem? . 16 3.2 Prime Numbers . 17 3.2.1 Largest known Mersenne prime . 17 3.2.2 Largest known prime . 17 3.2.3 Largest known twin primes . 18 3.2.4 Largest Fermat number with known factorization . 18 3.2.5 Algorithms to factor integer numbers . 18 3.2.6 Primality Testing . 19 3.2.7 List of record numbers . 20 3.2.8 What is the current status on Mersenne primes? . -
Puzzling Game of Life” Production Notes -Page 1
“The Puzzling Game of Life” Production Notes -Page 1 THE PUZZLING GAME OF LIFE Production Notes A four-act skit, using various game show formats to provide the setting for the main character to progress in her spiritual journey. SUMMARY: Suzy Christian finds herself on a journey in “The Game of Life.” Each game show that she participates in is another step in her spiritual journey, where she faces trials and temptations as well as growth and victory.. THEME: The retreat theme was “God Meant It For Good” and the theme verse was Romans 8:28. The visual theme was puzzle pieces, all fitting together. In this skit, we see puzzling things happening to Suzy Christian, and she doesn’t understand why she is experiencing trials. But the skit attempts to show how God is using even those difficult experiences in our life for our good and the good of others. THEME VERSE: “And we know that all things work together for good to those who love God, to those who are the called according to His purpose.” Romans 8:28 CHARACTERS: (Note: There are only a few main characters in this skit (marked with asterisk (*). All of the remaining characters are minor characters. One person could easily take the role of one of the minor characters in each act. But this is a great opportunity to assign small roles, appearing in only one act, to people and see how they handle being on stage.) *Rod Sterling Narrator *Guy Smiley - obnoxious game show host, who greatly exaggerates some of his lines (which are capitalized in the script) in a sarcastic manner *Suzy Christian - a woman, wife and mother who has recently become a Christian. -
Discrete Probability Distributions Random Variables
Discrete Probability Distributions Random Variables • A variable that associates a number with the outcome of a random experiment is called a random variable. • Notation: random variable is denoted by an uppercase letter, such as X. After the experiment is conducted, the measured value is denoted by a lowercase letter, such a x. Both X and x are shown in italics, e.g., P(X=x). Sec 2‐8 Random Variables 2 Continuous & Discrete Random Variables • A discrete random variable is usually integer number – N ‐ the number of p53 proteins in a cell – D ‐ the number of nucleotides different between two sequences • A continuous random variable is a real number – C=N/V – the concentration of p53 protein in a cell of volume V – Percentage (D/L)*100% of different nucleotides in protein sequences of different lengths L (depending on the set of L’s may be discrete but dense) Sec 2‐8 Random Variables 3 Probability Mass Function (PMF) • I want to compare all 4‐ mers in a pair of human genomes • X – random variable: the number of nucleotide Probability Mass Function for differences in a given 4‐ the # of mismatches in 4‐mers mer P(X =0) = 0.6561 • Probability Mass Function: P(X =1) = 0.2916 f(x) or P(X=x) –the P(X =2) = 0.0486 probability that the # of P(X =3) = 0.0036 P(X =4) = 0.0001 SNPs is exactly equal to x Σx P(X=x)= 1.0000 4 Cumulative Distribution Function (CDF) P(X≤x) P(X>x) 0.6561 0.3439 0.9477 0.0523 0.9963 0.0037 0.9999 0.0001 1.0000 0.0000 CDF: P(X ≤ 3) = P(X=0) + P(X=1) + P(X=2) + P(X=3) = 0.9999 Complementary cumulative distribution function (tail distribution) CCDF: P(X >3) =1‐ P(X ≤ 3) =0.0001 5 Mean or Expected Value of X The mean or expected value of the discrete random variable X, denoted as or EX, is EX xPX x xf x xx • The mean = the weighted average of all possible values of X. -
The Monty Hall Problem in the Game Theory Class
The Monty Hall Problem in the Game Theory Class Sasha Gnedin∗ October 29, 2018 1 Introduction Suppose you’re on a game show, and you’re given the choice of three doors: Behind one door is a car; behind the others, goats. You pick a door, say No. 1, and the host, who knows what’s behind the doors, opens another door, say No. 3, which has a goat. He then says to you, “Do you want to pick door No. 2?” Is it to your advantage to switch your choice? With these famous words the Parade Magazine columnist vos Savant opened an exciting chapter in mathematical didactics. The puzzle, which has be- come known as the Monty Hall Problem (MHP), has broken the records of popularity among the probability paradoxes. The book by Rosenhouse [9] and the Wikipedia entry on the MHP present the history and variations of the problem. arXiv:1107.0326v1 [math.HO] 1 Jul 2011 In the basic version of the MHP the rules of the game specify that the host must always reveal one of the unchosen doors to show that there is no prize there. Two remaining unrevealed doors may hide the prize, creating the illusion of symmetry and suggesting that the action does not matter. How- ever, the symmetry is fallacious, and switching is a better action, doubling the probability of winning. There are two main explanations of the paradox. One of them, simplistic, amounts to just counting the mutually exclusive cases: either you win with ∗[email protected] 1 switching or with holding the first choice. -
Game, Set, and Match Carl W
Game, Set, and Match Carl W. Lee September 2016 Note: Some of the text below comes from Martin Gardner's articles in Scientific American and some from Mathematical Circles by Fomin, Genkin, and Itenberg. 1 1 Fifteen This is a two player game. Take a set of nine cards, numbered one (ace) through nine. They are spread out on the table, face up. Players alternately select a card to add their hands, which they keep face up in front of them. The goal is to achieve a subset of three cards in your hand so that the values of these three cards sum to exactly fifteen. (The ace counts as 1.) This is an example of a game that is isomorphic to (the \same as") a well-known game: Tic-Tac-Toe. Number the cells of a tic-tac-toe board with the integers from 1 to 9 arranged in the form of a magic square. 8 1 6 3 5 7 4 9 2 Then winning combinations correspond exactly to triples of numbers that sum to 15. This is a combinatorial two person game (but one that permits ties). There is no hidden information (e.g., cards that one player has that the other cannot see) and no random elements (e.g., rolling of dice). 2 2 Ones and Twos Ten 1's and ten 2's are written on a blackboard. In one turn, a player may erase (or cross out) any two numbers. If the two numbers erased are identical, they are replaced with a single 2. -
Introduction to Probability 1 Monty Hall
Massachusetts Institute of Technology Course Notes, Week 12 6.042J/18.062J, Fall ’05: Mathematics for Computer Science November 21 Prof. Albert R. Meyer and Prof. Ronitt Rubinfeld revised November 29, 2005, 1285 minutes Introduction to Probability Probability is the last topic in this course and perhaps the most important. Many algo rithms rely on randomization. Investigating their correctness and performance requires probability theory. Moreover, many aspects of computer systems, such as memory man agement, branch prediction, packet routing, and load balancing are designed around probabilistic assumptions and analyses. Probability also comes up in information theory, cryptography, artificial intelligence, and game theory. Beyond these engineering applica tions, an understanding of probability gives insight into many everyday issues, such as polling, DNA testing, risk assessment, investing, and gambling. So probability is good stuff. 1 Monty Hall In the September 9, 1990 issue of Parade magazine, the columnist Marilyn vos Savant responded to this letter: Suppose you’re on a game show, and you’re given the choice of three doors. Behind one door is a car, behind the others, goats. You pick a door, say number 1, and the host, who knows what’s behind the doors, opens another door, say number 3, which has a goat. He says to you, ”Do you want to pick door number 2?” Is it to your advantage to switch your choice of doors? Craig. F. Whitaker Columbia, MD The letter roughly describes a situation faced by contestants on the 1970’s game show Let’s Make a Deal, hosted by Monty Hall and Carol Merrill. -
Introduction to Game Theory I
Introduction to Game Theory I Presented To: 2014 Summer REU Penn State Department of Mathematics Presented By: Christopher Griffin [email protected] 1/34 Types of Game Theory GAME THEORY Classical Game Combinatorial Dynamic Game Evolutionary Other Topics in Theory Game Theory Theory Game Theory Game Theory No time, doesn't contain differential equations Notion of time, may contain differential equations Games with finite or Games with no Games with time. Modeling population Experimental / infinite strategy space, chance. dynamics under Behavioral Game but no time. Games with motion or competition Theory Generally two player a dynamic component. Games with probability strategic games Modeling the evolution Voting Theory (either induced by the played on boards. Examples: of strategies in a player or the game). Optimal play in a dog population. Examples: Moves change the fight. Chasing your Determining why Games with coalitions structure of a game brother across a room. Examples: altruism is present in or negotiations. board. The evolution of human society. behaviors in a group of Examples: Examples: animals. Determining if there's Poker, Strategic Chess, Checkers, Go, a fair voting system. Military Decision Nim. Equilibrium of human Making, Negotiations. behavior in social networks. 2/34 Games Against the House The games we often see on television fall into this category. TV Game Shows (that do not pit players against each other in knowledge tests) often require a single player (who is, in a sense, playing against The House) to make a decision that will affect only his life. Prize is Behind: 1 2 3 Choose Door: 1 2 3 1 2 3 1 2 3 Switch: Y N Y N Y N Y N Y N Y N Y N Y N Y N Win/Lose: L W W L W L W L L W W L W L W L L W The Monty Hall Problem Other games against the house: • Blackjack • The Price is Right 3/34 Assumptions of Multi-Player Games 1. -
The Monty Hall Problem Yurixy Lopez Martinez a Project Presented for The
The Monty Hall Problem Yurixy Lopez Martinez A project presented for the degree of Bachelors of Arts, Mathematics Mathematics Department Whitman College Walla Walla, WA May 10, 2019 Abstract This paper begins by offering a detailed explanation of the solution to the Monty Hall Problem utilizing decision trees and mathematical concepts of conditional probability, mainly Bayes' Theorem. We will proceed to investigate the various versions of the problem that have risen throughout the years among scholars, mainly focusing on the benefits of a particular strategies. We will conclude by briefly discussing some applications of the Monty Hall Problem to other disciplines, mainly the probabilistic aspects. 1 Contents 1 Introduction 3 2 Monty Hall Problem 4 3 Why Switch? 5 4 Conditional Probability: Bayes' Theorem 7 5 Bayesian Monty 9 6 Variations of the Monty Hall Problem 10 6.1 Monty Chooses Randomly . 10 6.2 Highest-Ordered Selection . 11 6.3 Many doors . 14 6.3.1 Alternative Solution . 16 6.4 Many Doors, Many Cars . 17 6.5 Random Car Placement . 18 6.6 Two Contestants . 19 7 Applications of Monty Hall Problem 19 7.1 Philosophy . 20 7.2 Physics . 20 7.3 Economics . 21 7.4 Cognitive Science and Psychology . 21 8 Conclusion 21 9 Acknowledgements 22 2 1 Introduction The Monty Hall Problem is a recognized probability problem. The canonical, classical version of the problem is described as follows: A contestant is shown three identical doors. Behind one of them is a car. The other two conceal goats. The contestant is asked to choose, but not open, one of the doors. -
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Responses to Modified Monty Hall Dilemmas in Capuchin Monkeys, Rhesus Macaques, and Humans
2018, 31 David Washburn Special Issue Editor** Peer-reviewed Responses to Modified Monty Hall Dilemmas in Capuchin Monkeys, Rhesus Macaques, and Humans Julia Watzek*1, Will Whitham1, David A. Washburn1-2, and Sarah F. Brosnan1-3 1Department of Psychology, Language Research Center, Georgia State University 2Neuroscience Institute, Georgia State University 3Department of Philosophy, Center for Behavioral Neuroscience, Georgia State University The Monty Hall Dilemma (MHD) is a simple probability puzzle famous for its counterintuitive solution. Participants initially choose among three doors, one of which conceals a prize. A different door is opened and shown not to contain the prize. Participants are then asked whether they would like to stay with their original choice or switch to the other remaining door. Although switching doubles the chances of winning, people overwhelmingly choose to stay with their original choice. To assess how experience and the chance of winning affect decisions in the MHD, we used a comparative approach to test 264 college students, 24 capuchin monkeys, and 7 rhesus macaques on a nonverbal, computerized version of the game. Participants repeatedly experienced the outcome of their choices and we varied the chance of winning by changing the number of doors (3 or 8). All species quickly and consistently switched doors, especially in the eight-door condition. After the computer task, we presented humans with the classic text version of the MHD to test whether they would generalize the successful switch strategy from the computer task. Instead, participants showed their characteristic tendency to stick with their pick, regardless of the number of doors. This disconnect between strategies in the classic version and a repeated nonverbal task with the same underlying probabilities may arise because they evoke different decision-making processes, such as explicit reasoning versus implicit learning.