Determinacy Maximum
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Lecture 4 Rationalizability & Nash Equilibrium Road
Lecture 4 Rationalizability & Nash Equilibrium 14.12 Game Theory Muhamet Yildiz Road Map 1. Strategies – completed 2. Quiz 3. Dominance 4. Dominant-strategy equilibrium 5. Rationalizability 6. Nash Equilibrium 1 Strategy A strategy of a player is a complete contingent-plan, determining which action he will take at each information set he is to move (including the information sets that will not be reached according to this strategy). Matching pennies with perfect information 2’s Strategies: HH = Head if 1 plays Head, 1 Head if 1 plays Tail; HT = Head if 1 plays Head, Head Tail Tail if 1 plays Tail; 2 TH = Tail if 1 plays Head, 2 Head if 1 plays Tail; head tail head tail TT = Tail if 1 plays Head, Tail if 1 plays Tail. (-1,1) (1,-1) (1,-1) (-1,1) 2 Matching pennies with perfect information 2 1 HH HT TH TT Head Tail Matching pennies with Imperfect information 1 2 1 Head Tail Head Tail 2 Head (-1,1) (1,-1) head tail head tail Tail (1,-1) (-1,1) (-1,1) (1,-1) (1,-1) (-1,1) 3 A game with nature Left (5, 0) 1 Head 1/2 Right (2, 2) Nature (3, 3) 1/2 Left Tail 2 Right (0, -5) Mixed Strategy Definition: A mixed strategy of a player is a probability distribution over the set of his strategies. Pure strategies: Si = {si1,si2,…,sik} σ → A mixed strategy: i: S [0,1] s.t. σ σ σ i(si1) + i(si2) + … + i(sik) = 1. If the other players play s-i =(s1,…, si-1,si+1,…,sn), then σ the expected utility of playing i is σ σ σ i(si1)ui(si1,s-i) + i(si2)ui(si2,s-i) + … + i(sik)ui(sik,s-i). -
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? . -
GTI Diagonalization
GTI Diagonalization A. Ada, K. Sutner Carnegie Mellon University Fall 2017 1 Comments Cardinality Infinite Cardinality Diagonalization Personal Quirk 1 3 “Theoretical Computer Science (TCS)” sounds distracting–computers are just a small part of the story. I prefer Theory of Computation (ToC) and will refer to that a lot. ToC: computability theory complexity theory proof theory type theory/set theory physical realizability Personal Quirk 2 4 To my mind, the exact relationship between physics and computation is an absolutely fascinating open problem. It is obvious that the standard laws of physics support computation (ignoring resource bounds). There even are people (Landauer 1996) who claim . this amounts to an assertion that mathematics and com- puter science are a part of physics. I think that is total nonsense, but note that Landauer was no chump: in fact, he was an excellent physicists who determined the thermodynamical cost of computation and realized that reversible computation carries no cost. At any rate . Note the caveat: “ignoring resource bounds.” Just to be clear: it is not hard to set up computations that quickly overpower the whole (observable) physical universe. Even a simple recursion like this one will do. A(0, y) = y+ A(x+, 0) = A(x, 1) A(x+, y+) = A(x, A(x+, y)) This is the famous Ackermann function, and I don’t believe its study is part of physics. And there are much worse examples. But the really hard problem is going in the opposite direction: no one knows how to axiomatize physics in its entirety, so one cannot prove that all physical processes are computable. -
Is Uncountable the Open Interval (0, 1)
Section 2.4:R is uncountable (0, 1) is uncountable This assertion and its proof date back to the 1890’s and to Georg Cantor. The proof is often referred to as “Cantor’s diagonal argument” and applies in more general contexts than we will see in these notes. Our goal in this section is to show that the setR of real numbers is uncountable or non-denumerable; this means that its elements cannot be listed, or cannot be put in bijective correspondence with the natural numbers. We saw at the end of Section 2.3 that R has the same cardinality as the interval ( π , π ), or the interval ( 1, 1), or the interval (0, 1). We will − 2 2 − show that the open interval (0, 1) is uncountable. Georg Cantor : born in St Petersburg (1845), died in Halle (1918) Theorem 42 The open interval (0, 1) is not a countable set. Dr Rachel Quinlan MA180/MA186/MA190 Calculus R is uncountable 143 / 222 Dr Rachel Quinlan MA180/MA186/MA190 Calculus R is uncountable 144 / 222 The open interval (0, 1) is not a countable set A hypothetical bijective correspondence Our goal is to show that the interval (0, 1) cannot be put in bijective correspondence with the setN of natural numbers. Our strategy is to We recall precisely what this set is. show that no attempt at constructing a bijective correspondence between It consists of all real numbers that are greater than zero and less these two sets can ever be complete; it can never involve all the real than 1, or equivalently of all the points on the number line that are numbers in the interval (0, 1) no matter how it is devised. -
SEQUENTIAL GAMES with PERFECT INFORMATION Example
SEQUENTIAL GAMES WITH PERFECT INFORMATION Example 4.9 (page 105) Consider the sequential game given in Figure 4.9. We want to apply backward induction to the tree. 0 Vertex B is owned by player two, P2. The payoffs for P2 are 1 and 3, with 3 > 1, so the player picks R . Thus, the payoffs at B become (0, 3). 00 Next, vertex C is also owned by P2 with payoffs 1 and 0. Since 1 > 0, P2 picks L , and the payoffs are (4, 1). Player one, P1, owns A; the choice of L gives a payoff of 0 and R gives a payoff of 4; 4 > 0, so P1 chooses R. The final payoffs are (4, 1). 0 00 We claim that this strategy profile, { R } for P1 and { R ,L } is a Nash equilibrium. Notice that the 0 00 strategy profile gives a choice at each vertex. For the strategy { R ,L } fixed for P2, P1 has a maximal payoff by choosing { R }, ( 0 00 0 00 π1(R, { R ,L }) = 4 π1(R, { R ,L }) = 4 ≥ 0 00 π1(L, { R ,L }) = 0. 0 00 In the same way, for the strategy { R } fixed for P1, P2 has a maximal payoff by choosing { R ,L }, ( 00 0 00 π2(R, {∗,L }) = 1 π2(R, { R ,L }) = 1 ≥ 00 π2(R, {∗,R }) = 0, where ∗ means choose either L0 or R0. Since no change of choice by a player can increase that players own payoff, the strategy profile is called a Nash equilibrium. Notice that the above strategy profile is also a Nash equilibrium on each branch of the game tree, mainly starting at either B or starting at C. -
Cardinality of Accumulation Points of Infinite Sets 1 Introduction
International Mathematical Forum, Vol. 11, 2016, no. 11, 539 - 546 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/imf.2016.6224 Cardinality of Accumulation Points of Infinite Sets A. Kalapodi CTI Diophantus, Computer Technological Institute & Press University Campus of Patras, 26504 Patras, Greece Copyright c 2016 A. Kalapodi. This article is distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract One of the fundamental theorems in real analysis is the Bolzano- Weierstrass property according to which every bounded infinite set of real numbers has an accumulation point. Since this theorem essentially asserts the completeness of the real numbers, the notion of accumulation point becomes substantial. This work provides an efficient number of examples which cover every possible case in the study of accumulation points, classifying the different sizes of the derived set A0 and of the sets A \ A0, A0 n A, for an infinite set A. Mathematics Subject Classification: 97E60, 97I30 Keywords: accumulation point; derived set; countable set; uncountable set 1 Introduction The \accumulation point" is a mathematical notion due to Cantor ([2]) and although it is fundamental in real analysis, it is also important in other areas of pure mathematics, such as the study of metric or topological spaces. Following the usual notation for a metric space (X; d), we denote by V (x0;") = fx 2 X j d(x; x0) < "g the open sphere of center x0 and radius " and by D(x0;") the set V (x0;") n fx0g. -
Subgame-Perfect Ε-Equilibria in Perfect Information Games With
Subgame-Perfect -Equilibria in Perfect Information Games with Common Preferences at the Limit Citation for published version (APA): Flesch, J., & Predtetchinski, A. (2016). Subgame-Perfect -Equilibria in Perfect Information Games with Common Preferences at the Limit. Mathematics of Operations Research, 41(4), 1208-1221. https://doi.org/10.1287/moor.2015.0774 Document status and date: Published: 01/11/2016 DOI: 10.1287/moor.2015.0774 Document Version: Publisher's PDF, also known as Version of record Document license: Taverne Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. -
Cardinality of Sets
Cardinality of Sets MAT231 Transition to Higher Mathematics Fall 2014 MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 1 / 15 Outline 1 Sets with Equal Cardinality 2 Countable and Uncountable Sets MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 2 / 15 Sets with Equal Cardinality Definition Two sets A and B have the same cardinality, written jAj = jBj, if there exists a bijective function f : A ! B. If no such bijective function exists, then the sets have unequal cardinalities, that is, jAj 6= jBj. Another way to say this is that jAj = jBj if there is a one-to-one correspondence between the elements of A and the elements of B. For example, to show that the set A = f1; 2; 3; 4g and the set B = {♠; ~; }; |g have the same cardinality it is sufficient to construct a bijective function between them. 1 2 3 4 ♠ ~ } | MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 3 / 15 Sets with Equal Cardinality Consider the following: This definition does not involve the number of elements in the sets. It works equally well for finite and infinite sets. Any bijection between the sets is sufficient. MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 4 / 15 The set Z contains all the numbers in N as well as numbers not in N. So maybe Z is larger than N... On the other hand, both sets are infinite, so maybe Z is the same size as N... This is just the sort of ambiguity we want to avoid, so we appeal to the definition of \same cardinality." The answer to our question boils down to \Can we find a bijection between N and Z?" Does jNj = jZj? True or false: Z is larger than N. -
Axiomatic Set Teory P.D.Welch
Axiomatic Set Teory P.D.Welch. August 16, 2020 Contents Page 1 Axioms and Formal Systems 1 1.1 Introduction 1 1.2 Preliminaries: axioms and formal systems. 3 1.2.1 The formal language of ZF set theory; terms 4 1.2.2 The Zermelo-Fraenkel Axioms 7 1.3 Transfinite Recursion 9 1.4 Relativisation of terms and formulae 11 2 Initial segments of the Universe 17 2.1 Singular ordinals: cofinality 17 2.1.1 Cofinality 17 2.1.2 Normal Functions and closed and unbounded classes 19 2.1.3 Stationary Sets 22 2.2 Some further cardinal arithmetic 24 2.3 Transitive Models 25 2.4 The H sets 27 2.4.1 H - the hereditarily finite sets 28 2.4.2 H - the hereditarily countable sets 29 2.5 The Montague-Levy Reflection theorem 30 2.5.1 Absoluteness 30 2.5.2 Reflection Theorems 32 2.6 Inaccessible Cardinals 34 2.6.1 Inaccessible cardinals 35 2.6.2 A menagerie of other large cardinals 36 3 Formalising semantics within ZF 39 3.1 Definite terms and formulae 39 3.1.1 The non-finite axiomatisability of ZF 44 3.2 Formalising syntax 45 3.3 Formalising the satisfaction relation 46 3.4 Formalising definability: the function Def. 47 3.5 More on correctness and consistency 48 ii iii 3.5.1 Incompleteness and Consistency Arguments 50 4 The Constructible Hierarchy 53 4.1 The L -hierarchy 53 4.2 The Axiom of Choice in L 56 4.3 The Axiom of Constructibility 57 4.4 The Generalised Continuum Hypothesis in L. -
Are Large Cardinal Axioms Restrictive?
Are Large Cardinal Axioms Restrictive? Neil Barton∗ 24 June 2020y Abstract The independence phenomenon in set theory, while perva- sive, can be partially addressed through the use of large cardinal axioms. A commonly assumed idea is that large cardinal axioms are species of maximality principles. In this paper, I argue that whether or not large cardinal axioms count as maximality prin- ciples depends on prior commitments concerning the richness of the subset forming operation. In particular I argue that there is a conception of maximality through absoluteness, on which large cardinal axioms are restrictive. I argue, however, that large cardi- nals are still important axioms of set theory and can play many of their usual foundational roles. Introduction Large cardinal axioms are widely viewed as some of the best candi- dates for new axioms of set theory. They are (apparently) linearly ordered by consistency strength, have substantial mathematical con- sequences for questions independent from ZFC (such as consistency statements and Projective Determinacy1), and appear natural to the ∗Fachbereich Philosophie, University of Konstanz. E-mail: neil.barton@uni- konstanz.de. yI would like to thank David Aspero,´ David Fernandez-Bret´ on,´ Monroe Eskew, Sy-David Friedman, Victoria Gitman, Luca Incurvati, Michael Potter, Chris Scam- bler, Giorgio Venturi, Matteo Viale, Kameryn Williams and audiences in Cambridge, New York, Konstanz, and Sao˜ Paulo for helpful discussion. Two anonymous ref- erees also provided helpful comments, and I am grateful for their input. I am also very grateful for the generous support of the FWF (Austrian Science Fund) through Project P 28420 (The Hyperuniverse Programme) and the VolkswagenStiftung through the project Forcing: Conceptual Change in the Foundations of Mathematics. -
17 Axiom of Choice
Math 361 Axiom of Choice 17 Axiom of Choice De¯nition 17.1. Let be a nonempty set of nonempty sets. Then a choice function for is a function f sucFh that f(S) S for all S . F 2 2 F Example 17.2. Let = (N)r . Then we can de¯ne a choice function f by F P f;g f(S) = the least element of S: Example 17.3. Let = (Z)r . Then we can de¯ne a choice function f by F P f;g f(S) = ²n where n = min z z S and, if n = 0, ² = min z= z z = n; z S . fj j j 2 g 6 f j j j j j 2 g Example 17.4. Let = (Q)r . Then we can de¯ne a choice function f as follows. F P f;g Let g : Q N be an injection. Then ! f(S) = q where g(q) = min g(r) r S . f j 2 g Example 17.5. Let = (R)r . Then it is impossible to explicitly de¯ne a choice function for . F P f;g F Axiom 17.6 (Axiom of Choice (AC)). For every set of nonempty sets, there exists a function f such that f(S) S for all S . F 2 2 F We say that f is a choice function for . F Theorem 17.7 (AC). If A; B are non-empty sets, then the following are equivalent: (a) A B ¹ (b) There exists a surjection g : B A. ! Proof. (a) (b) Suppose that A B. -
Formal Construction of a Set Theory in Coq
Saarland University Faculty of Natural Sciences and Technology I Department of Computer Science Masters Thesis Formal Construction of a Set Theory in Coq submitted by Jonas Kaiser on November 23, 2012 Supervisor Prof. Dr. Gert Smolka Advisor Dr. Chad E. Brown Reviewers Prof. Dr. Gert Smolka Dr. Chad E. Brown Eidesstattliche Erklarung¨ Ich erklare¨ hiermit an Eides Statt, dass ich die vorliegende Arbeit selbststandig¨ verfasst und keine anderen als die angegebenen Quellen und Hilfsmittel verwendet habe. Statement in Lieu of an Oath I hereby confirm that I have written this thesis on my own and that I have not used any other media or materials than the ones referred to in this thesis. Einverstandniserkl¨ arung¨ Ich bin damit einverstanden, dass meine (bestandene) Arbeit in beiden Versionen in die Bibliothek der Informatik aufgenommen und damit vero¨ffentlicht wird. Declaration of Consent I agree to make both versions of my thesis (with a passing grade) accessible to the public by having them added to the library of the Computer Science Department. Saarbrucken,¨ (Datum/Date) (Unterschrift/Signature) iii Acknowledgements First of all I would like to express my sincerest gratitude towards my advisor, Chad Brown, who supported me throughout this work. His extensive knowledge and insights opened my eyes to the beauty of axiomatic set theory and foundational mathematics. We spent many hours discussing the minute details of the various constructions and he taught me the importance of mathematical rigour. Equally important was the support of my supervisor, Prof. Smolka, who first introduced me to the topic and was there whenever a question arose.