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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. -
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? . -
QUARTIC CM FIELDS 1. Background the Study of Complex Multiplication
QUARTIC CM FIELDS WENHAN WANG Abstract. In the article, we describe the basic properties, general and specific properties of CM degree 4 fields, as well as illustrating their connection to the study of genus 2 curves with CM. 1. Background The study of complex multiplication is closely related to the study of curves over finite fields and their Jacobian. Basically speaking, for the case of non-supersingular elliptic curves over finite fields, the endomorphism ring is ring-isomorphic to an order in an imaginary quadratic extension K of Q. The structure of imaginary extensions of Q has beenp thoroughly studied, and the ringsq of integers are simply generated by f1; Dg if D ≡ 1 mod 4, f D g ≡ or by 1; 4 if D 0 mod 4, where D is the discriminant of the field K. The theory of complex multiplication can be carried from elliptic curves to the (Jacobians) of genus 2 (hyperelliptic) curves. More explicitly, the Jacobian of any non-supersingular genus 2 (and hence, hyperelliptic) curve defined over a finite field has CM by an order in a degree 4, or quartic extension over Q, where the extension field K has to be totally imaginary. Description of the endomorphism ring of the Jacobian of a genus 2 curve over a finite field largely depends on the field K for which the curve has CM by. Many articles in the area of the study of genus two curves lead to the study of many properties of the field K. Hence the main goal of this article is, based on the knowledge of the author in the study of the genus 2 curves over finite fields, to give a survey of various, general or specific, properties of degree 4 CM fields. -
Properties of N-Sided Regular Polygons
PROPERTIES OF N-SIDED REGULAR POLYGONS When students are first exposed to regular polygons in middle school, they learn their properties by looking at individual examples such as the equilateral triangles(n=3), squares(n=4), and hexagons(n=6). A generalization is usually not given, although it would be straight forward to do so with just a min imum of trigonometry and algebra. It also would help students by showing how one obtains generalization in mathematics. We show here how to carry out such a generalization for regular polynomials of side length s. Our starting point is the following schematic of an n sided polygon- We see from the figure that any regular n sided polygon can be constructed by looking at n isosceles triangles whose base angles are θ=(1-2/n)(π/2) since the vertex angle of the triangle is just ψ=2π/n, when expressed in radians. The area of the grey triangle in the above figure is- 2 2 ATr=sh/2=(s/2) tan(θ)=(s/2) tan[(1-2/n)(π/2)] so that the total area of any n sided regular convex polygon will be nATr, , with s again being the side-length. With this generalized form we can construct the following table for some of the better known regular polygons- Name Number of Base Angle, Non-Dimensional 2 sides, n θ=(π/2)(1-2/n) Area, 4nATr/s =tan(θ) Triangle 3 π/6=30º 1/sqrt(3) Square 4 π/4=45º 1 Pentagon 5 3π/10=54º sqrt(15+20φ) Hexagon 6 π/3=60º sqrt(3) Octagon 8 3π/8=67.5º 1+sqrt(2) Decagon 10 2π/5=72º 10sqrt(3+4φ) Dodecagon 12 5π/12=75º 144[2+sqrt(3)] Icosagon 20 9π/20=81º 20[2φ+sqrt(3+4φ)] Here φ=[1+sqrt(5)]/2=1.618033989… is the well known Golden Ratio. -
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. -
The Kronecker-Weber Theorem
The Kronecker-Weber Theorem Lucas Culler Introduction The Kronecker-Weber theorem is one of the earliest known results in class field theory. It says: Theorem. (Kronecker-Weber-Hilbert) Every abelian extension of the rational numbers Q is con- tained in a cyclotomic extension. Recall that an abelian extension is a finite field extension K/Q such that the galois group Gal(K/Q) th is abelian, and a cyclotomic extension is an extension of the form Q(ζ), where ζ is an n root of unity. This paper consists of two proofs of the Kronecker-Weber theorem. The first is rather involved, but elementary, and uses the theory of higher ramification groups. The second is a simple application of the main results of class field theory, which classifies abelian extension of an arbitrary number field. An Elementary Proof Now we will present an elementary proof of the Kronecker-Weber theoerem, in the spirit of Hilbert’s original proof. The particular strategy used here is given as a series of exercises in Marcus [1]. Minkowski’s Theorem We first prove a classical result due to Minkowski. Theorem. (Minkowski) Any finite extension of Q has nonzero discriminant. In particular, such an extension is ramified at some prime p ∈ Z. Proof. Let K/Q be a finite extension of degree n, and let A = OK be its ring of integers. Consider the embedding: r s A −→ R ⊕ C x 7→ (σ1(x), ..., σr(x), τ1(x), ..., τs(x)) where the σi are the real embeddings of K and the τi are the complex embeddings, with one embedding chosen from each conjugate pair, so that n = r + 2s. -
Lecture 9: Newton Method 9.1 Motivation 9.2 History
10-725: Convex Optimization Fall 2013 Lecture 9: Newton Method Lecturer: Barnabas Poczos/Ryan Tibshirani Scribes: Wen-Sheng Chu, Shu-Hao Yu Note: LaTeX template courtesy of UC Berkeley EECS dept. 9.1 Motivation Newton method is originally developed for finding a root of a function. It is also known as Newton- Raphson method. The problem can be formulated as, given a function f : R ! R, finding the point x? such that f(x?) = 0. Figure 9.1 illustrates another motivation of Newton method. Given a function f, we want to approximate it at point x with a quadratic function fb(x). We move our the next step determined by the optimum of fb. Figure 9.1: Motivation for quadratic approximation of a function. 9.2 History Babylonian people first applied the Newton method to find the square root of a positive number S 2 R+. The problem can be posed as solving the equation f(x) = x2 − S = 0. They realized the solution can be achieved by applying the iterative update rule: 2 1 S f(xk) xk − S xn+1 = (xk + ) = xk − 0 = xk − : (9.1) 2 xk f (xk) 2xk This update rule converges to the square root of S, which turns out to be a special case of Newton method. This could be the first application of Newton method. The starting point affects the convergence of the Babylonian's method for finding the square root. Figure 9.2 shows an example of solving the square root for S = 100. x- and y-axes represent the number of iterations and the variable, respectively. -
Formulas Involving Polygons - Lesson 7-3
you are here > Class Notes – Chapter 7 – Lesson 7-3 Formulas Involving Polygons - Lesson 7-3 Here’s today’s warmup…don’t forget to “phone home!” B Given: BD bisects ∠PBQ PD ⊥ PB QD ⊥ QB M Prove: BD is ⊥ bis. of PQ P Q D Statements Reasons Honors Geometry Notes Today, we started by learning how polygons are classified by their number of sides...you should already know a lot of these - just make sure to memorize the ones you don't know!! Sides Name 3 Triangle 4 Quadrilateral 5 Pentagon 6 Hexagon 7 Heptagon 8 Octagon 9 Nonagon 10 Decagon 11 Undecagon 12 Dodecagon 13 Tridecagon 14 Tetradecagon 15 Pentadecagon 16 Hexadecagon 17 Heptadecagon 18 Octadecagon 19 Enneadecagon 20 Icosagon n n-gon Baroody Page 2 of 6 Honors Geometry Notes Next, let’s look at the diagonals of polygons with different numbers of sides. By drawing as many diagonals as we could from one diagonal, you should be able to see a pattern...we can make n-2 triangles in a n-sided polygon. Given this information and the fact that the sum of the interior angles of a polygon is 180°, we can come up with a theorem that helps us to figure out the sum of the measures of the interior angles of any n-sided polygon! Baroody Page 3 of 6 Honors Geometry Notes Next, let’s look at exterior angles in a polygon. First, consider the exterior angles of a pentagon as shown below: Note that the sum of the exterior angles is 360°. -
DRAFT Uncountable Problems 1. Introduction
November 8, 9, 2017; June 10, 21, November 8, 2018; January 19, 2019. DRAFT Chapter from a book, The Material Theory of Induction, now in preparation. Uncountable Problems John D. Norton1 Department of History and Philosophy of Science University of Pittsburgh http://www.pitt.edu/~jdnorton 1. Introduction The previous chapter examined the inductive logic applicable to an infinite lottery machine. Such a machine generates a countably infinite set of outcomes, that is, there are as many outcomes as natural numbers, 1, 2, 3, … We found there that, if the lottery machine is to operate without favoring any particular outcome, the inductive logic native to the system is not probabilistic. A countably infinite set is the smallest in the hierarchy of infinities. The next routinely considered is a continuum-sized set, such as given by the set of all real numbers or even just by the set of all real numbers in some interval, from, say, 0 to 1. It is easy to fall into thinking that the problems of inductive inference with countably infinite sets do not arise for outcome sets of continuum size. For a familiar structure in probability theory is the uniform distribution of probabilities over some interval of real numbers. One might think that this probability distribution provides a logic that treats each outcome in a continuum-sized set equally, thereby doing what no probability distribution could do for a countably infinite set. That would be a mistake. A continuum-sized set is literally infinitely more complicated than a countably infinite set. If we simply ask that each outcome in a continuum- sized set be treated equally in the inductive logic, then just about every problem that arose with the countably infinite case reappears; and then more. -
Construction of Regular Polygons a Constructible Regular Polygon Is One That Can Be Constructed with Compass and (Unmarked) Straightedge
DynamicsOfPolygons.org Construction of regular polygons A constructible regular polygon is one that can be constructed with compass and (unmarked) straightedge. For example the construction on the right below consists of two circles of equal radii. The center of the second circle at B is chosen to lie anywhere on the first circle, so the triangle ABC is equilateral – and hence equiangular. Compass and straightedge constructions date back to Euclid of Alexandria who was born in about 300 B.C. The Greeks developed methods for constructing the regular triangle, square and pentagon, but these were the only „prime‟ regular polygons that they could construct. They also knew how to double the sides of a given polygon or combine two polygons together – as long as the sides were relatively prime, so a regular pentagon could be drawn together with a regular triangle to get a regular 15-gon. Therefore the polygons they could construct were of the form N = 2m3k5j where m is a nonnegative integer and j and k are either 0 or 1. The constructible regular polygons were 3, 4, 5, 6, 8, 10, 12, 15, 16, 20, 24, 30, 32, 40, 48, ... but the only odd polygons in this list are 3,5 and 15. The triangle, pentagon and 15-gon are the only regular polygons with odd sides which the Greeks could construct. If n = p1p2 …pk where the pi are odd primes then n is constructible iff each pi is constructible, so a regular 21-gon can be constructed iff both the triangle and regular 7-gon can be constructed. -
Functional Analysis
Functional Analysis Marco Di Francesco, Stefano Spirito 2 Contents I Introduction 5 1 Motivation 7 1.1 Someprerequisitesofsettheory. ............... 10 II Lebesgue integration 13 2 Introduction 15 2.1 Recalling Riemann integration . ............ 15 2.2 A new way to count rectangles: Lebesgue integration . .............. 17 3 An overview of Lebesgue measure theory 19 4 Lebesgue integration theory 23 4.1 Measurablefunctions................................. ............ 23 4.2 Simplefunctions ................................... ............ 24 4.3 Definition of the Lebesgue integral . ............ 25 5 Convergence properties of Lebesgue integral 31 5.1 Interchanging limits and integrals . ............... 31 5.2 Fubini’sTheorem................................... ............ 34 5.3 Egorov’s and Lusin’s Theorem. Convergence in measure . .............. 36 6 Exercises 39 III The basic principles of functional analysis 43 7 Metric spaces and normed spaces 45 7.1 Compactnessinmetricspaces. ............. 45 7.2 Introduction to Lp spaces .......................................... 48 7.3 Examples: some classical spaces of sequences . ............... 52 8 Linear operators 57 9 Hahn-Banach Theorems 59 9.1 The analytic form of the Hahn-Banach theorem . .......... 59 9.2 The geometric forms of the Hahn-Banach Theorem . .......... 61 10 The uniform boundedness principle and the closed graph theorem 65 10.1 The Baire category theorem . .......... 65 10.2 Theuniformboundednessprinciple . ................ 66 10.3 The open mapping theorem and the closed graph theorem . ............ 67 3 4 CONTENTS 11 Weak topologies 69 11.1 The inverse limit topology of a family of maps . ........... 69 11.2 The weak topology σ(E, E ∗) ........................................ 69 11.3 The weak ∗ topology σ(E∗, E )........................................ 73 11.4 Reflexive spaces and separable spaces . .............. 75 11.5 Uniformly Convex Space . .......... 78 12 Exercises 79 IV Lp spaces and Hilbert spaces 87 13 Lp spaces 89 p p 13.1 Density properties and separability of L spaces. -
Old Notes from Warwick, Part 1
Measure Theory, MA 359 Handout 1 Valeriy Slastikov Autumn, 2005 1 Measure theory 1.1 General construction of Lebesgue measure In this section we will do the general construction of σ-additive complete measure by extending initial σ-additive measure on a semi-ring to a measure on σ-algebra generated by this semi-ring and then completing this measure by adding to the σ-algebra all the null sets. This section provides you with the essentials of the construction and make some parallels with the construction on the plane. Throughout these section we will deal with some collection of sets whose elements are subsets of some fixed abstract set X. It is not necessary to assume any topology on X but for simplicity you may imagine X = Rn. We start with some important definitions: Definition 1.1 A nonempty collection of sets S is a semi-ring if 1. Empty set ? 2 S; 2. If A 2 S; B 2 S then A \ B 2 S; n 3. If A 2 S; A ⊃ A1 2 S then A = [k=1Ak, where Ak 2 S for all 1 ≤ k ≤ n and Ak are disjoint sets. If the set X 2 S then S is called semi-algebra, the set X is called a unit of the collection of sets S. Example 1.1 The collection S of intervals [a; b) for all a; b 2 R form a semi-ring since 1. empty set ? = [a; a) 2 S; 2. if A 2 S and B 2 S then A = [a; b) and B = [c; d).