A Defense of Logicism∗ and Theorems of Mathematics Are Derivable from Logical Truths and Ana- Lytic Truths
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Nominalism, Trivialism, Logicism
Nominalism, Trivialism, Logicism Agustín Rayo∗ May 1, 2014 This paper is an effort to extract some of the main theses in the philosophy of mathematics from my book, The Construction of Logical Space. I show that there are important limits to the availability of nominalistic paraphrase-functions for mathematical languages, and sug- gest a way around the problem by developing a method for specifying nominalistic contents without corresponding nominalistic paraphrases. Although much of the material in this paper is drawn from the book—and from an earlier paper (Rayo 2008)—I hope the present discussion will earn its keep by motivating the ideas in a new way, and by suggesting further applications. 1 Nominalism Mathematical Nominalism is the view that there are no mathematical objets. A standard problem for nominalists is that it is not obvious that they can explain what the point of a mathematical assertion would be. For it is natural to think that mathematical sentences like ‘the number of the dinosaurs is zero’ or ‘1 + 1 = 2’ can only be true if mathematical objects exist. But if this is right, the nominalist is committed to the view that such sentences are untrue. And if the sentences are untrue, it not immediately obvious why they would be worth asserting. ∗For their many helpful comments, I am indebted to Vann McGee, Kevin Richardson, Bernhard Salow and two anonymous referees for Philosophia Mathematica. I would also like to thank audiences at Smith College, the Università Vita-Salute San Raffaele, and MIT’s Logic, Langauge, Metaphysics and Mind Reading Group. Most of all, I would like to thank Steve Yablo. -
Biography Paper – Georg Cantor
Mike Garkie Math 4010 – History of Math UCD Denver 4/1/08 Biography Paper – Georg Cantor Few mathematicians are house-hold names; perhaps only Newton and Euclid would qualify. But there is a second tier of mathematicians, those whose names might not be familiar, but whose discoveries are part of everyday math. Examples here are Napier with logarithms, Cauchy with limits and Georg Cantor (1845 – 1918) with sets. In fact, those who superficially familier with Georg Cantor probably have two impressions of the man: First, as a consequence of thinking about sets, Cantor developed a theory of the actual infinite. And second, that Cantor was a troubled genius, crippled by Freudian conflict and mental illness. The first impression is fundamentally true. Cantor almost single-handedly overturned the Aristotle’s concept of the potential infinite by developing the concept of transfinite numbers. And, even though Bolzano and Frege made significant contributions, “Set theory … is the creation of one person, Georg Cantor.” [4] The second impression is mostly false. Cantor certainly did suffer from mental illness later in his life, but the other emotional baggage assigned to him is mostly due his early biographers, particularly the infamous E.T. Bell in Men Of Mathematics [7]. In the racially charged atmosphere of 1930’s Europe, the sensational story mathematician who turned the idea of infinity on its head and went crazy in the process, probably make for good reading. The drama of the controversy over Cantor’s ideas only added spice. 1 Fortunately, modern scholars have corrected the errors and biases in older biographies. -
Basic Concepts of Set Theory, Functions and Relations 1. Basic
Ling 310, adapted from UMass Ling 409, Partee lecture notes March 1, 2006 p. 1 Basic Concepts of Set Theory, Functions and Relations 1. Basic Concepts of Set Theory........................................................................................................................1 1.1. Sets and elements ...................................................................................................................................1 1.2. Specification of sets ...............................................................................................................................2 1.3. Identity and cardinality ..........................................................................................................................3 1.4. Subsets ...................................................................................................................................................4 1.5. Power sets .............................................................................................................................................4 1.6. Operations on sets: union, intersection...................................................................................................4 1.7 More operations on sets: difference, complement...................................................................................5 1.8. Set-theoretic equalities ...........................................................................................................................5 Chapter 2. Relations and Functions ..................................................................................................................6 -
Our Conceptual Understanding of a Phenomenon, While the Logic of Induction Adds Quantitative Details to the Conceptual Knowledge
DOCUMENT RESUME ED 376 173 TM 021 982 AUTHOR Ho, Yu Chong TITLE Abduction? Deduction? Induction? Is There a Logic of Exploratory Data Analysis? PUB DATE Apr 94 NOTE 28p.; Paper presented at the Annual Meeting of the American Educational Research Association (New Orleans, LA, April 4-8, 1994). PUB TYPE Reports Descriptive (141) Speeches/Conference Papers (150) EDRS PRICE MF01/PCO2 Plus Postage. DESCRIPTORS *Comprehension; *Deduction; Hypothesis Testing; *Induction; *Logic IDENTIFIERS *Abductive Reasoning; *Exploratory Data Analysis; Peirce (Charles S) ABSTRACT The philosophical notions introduced by Charles Sanders Peirce (1839-1914) are helpfu: for researchers in understanding the nature of knowledge and reality. In the Peircean logical system, the logic of abduction and deduction contribute to our conceptual understanding of a phenomenon, while the logic of induction adds quantitative details to the conceptual knowledge. Although Peirce justified the validity of induction as a self-corrective process, he asserted that neither induction nor deduction can help us to unveil the internal structure of meaning. As exploratory data analysis performs the function of a model builder for confirmatory data analysis, abduction plays the role of explorer of viable paths to further inquiry. Thus, the logic of abduction fits well into exploratory data analysis. At the stage of abduction, the goal is to explore the data, find out a pattern, and suggest a plausible hypothesis; deduction is to refine the hypothesis based upon other plausible premises; and induction is the empirical substantiation. (Contains 55 references.) (Author) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. is *********************************************************************** Abduction? Deduction? Induction? Is there a Logic of Exploratory Data Analysis? Yu Chong Ho University of Oklahoma Internet: [email protected] April 4, 1994 U S. -
(01.01.2020- 31.12.2020) Munich Center for Mathematical Philosophy
Academic Report for 2020 (01.01.2020- 31.12.2020) Since 2016 we provide access to more than 650 video recordings on virtually any kind of philosophical problem. Munich Center for Mathematical Philosophy 3. MCMP @ Facebook Prof. DDr. Hannes Leitgeb & Prof. Dr. Stephan Hartmann The MCMP regularly posts news and events on Facebook. Currently January 30, 2021 we have more than 3.300 people following our page, where we are This year has been exceptional and has shaken all of us from our usual sharing announcements and events. routines. With the appearance and spread of Coronavirus (Sars-CoV- 4. M-Phi Blog 2) the MCMP has followed the suggested rules and regulations by LMU Munich and the State of Bavaria. As a result, the centre was The MCMP maintains a blog on current topics in mathematical closed and everybody encouraged to work from home. Thanks to philosophy. everybody we could keep the spirit up and stay connected. 5. What’s Hot in Mathematical Philosophy? In this report, we present an overview of our activities in challenging 2020. Members of the MCMP are in charge of the “What’s Hot in Mathematical Philosophy?” series, which appears regularly in the (I) We continue to use different media in order to reach out to the online gazette The Reasoner. public: 6. Publication Management 1. The MCMP website In collaboration with LMU's library and the central internet After a relaunch and facelift, the MCMP website continues to be the department, we introduced our very own publication management place to go to for everything MCMP. -
Explanations
© Copyright, Princeton University Press. No part of this book may be distributed, posted, or reproduced in any form by digital or mechanical means without prior written permission of the publisher. CHAPTER 1 Explanations 1.1 SALLIES Language is an instrument of Logic, but not an indispensable instrument. Boole 1847a, 118 We know that mathematicians care no more for logic than logicians for mathematics. The two eyes of exact science are mathematics and logic; the mathematical sect puts out the logical eye, the logical sect puts out the mathematical eye; each believing that it sees better with one eye than with two. De Morgan 1868a,71 That which is provable, ought not to be believed in science without proof. Dedekind 1888a, preface If I compare arithmetic with a tree that unfolds upwards in a multitude of techniques and theorems whilst the root drives into the depthswx . Frege 1893a, xiii Arithmetic must be discovered in just the same sense in which Columbus discovered the West Indies, and we no more create numbers than he created the Indians. Russell 1903a, 451 1.2 SCOPE AND LIMITS OF THE BOOK 1.2.1 An outline history. The story told here from §3 onwards is re- garded as well known. It begins with the emergence of set theory in the 1870s under the inspiration of Georg Cantor, and the contemporary development of mathematical logic by Gottlob Frege andŽ. especially Giuseppe Peano. A cumulation of these and some related movements was achieved in the 1900s with the philosophy of mathematics proposed by Alfred North Whitehead and Bertrand Russell. -
The Development of Mathematical Logic from Russell to Tarski: 1900–1935
The Development of Mathematical Logic from Russell to Tarski: 1900–1935 Paolo Mancosu Richard Zach Calixto Badesa The Development of Mathematical Logic from Russell to Tarski: 1900–1935 Paolo Mancosu (University of California, Berkeley) Richard Zach (University of Calgary) Calixto Badesa (Universitat de Barcelona) Final Draft—May 2004 To appear in: Leila Haaparanta, ed., The Development of Modern Logic. New York and Oxford: Oxford University Press, 2004 Contents Contents i Introduction 1 1 Itinerary I: Metatheoretical Properties of Axiomatic Systems 3 1.1 Introduction . 3 1.2 Peano’s school on the logical structure of theories . 4 1.3 Hilbert on axiomatization . 8 1.4 Completeness and categoricity in the work of Veblen and Huntington . 10 1.5 Truth in a structure . 12 2 Itinerary II: Bertrand Russell’s Mathematical Logic 15 2.1 From the Paris congress to the Principles of Mathematics 1900–1903 . 15 2.2 Russell and Poincar´e on predicativity . 19 2.3 On Denoting . 21 2.4 Russell’s ramified type theory . 22 2.5 The logic of Principia ......................... 25 2.6 Further developments . 26 3 Itinerary III: Zermelo’s Axiomatization of Set Theory and Re- lated Foundational Issues 29 3.1 The debate on the axiom of choice . 29 3.2 Zermelo’s axiomatization of set theory . 32 3.3 The discussion on the notion of “definit” . 35 3.4 Metatheoretical studies of Zermelo’s axiomatization . 38 4 Itinerary IV: The Theory of Relatives and Lowenheim’s¨ Theorem 41 4.1 Theory of relatives and model theory . 41 4.2 The logic of relatives . -
Definitions and Nondefinability in Geometry 475 2
Definitions and Nondefinability in Geometry1 James T. Smith Abstract. Around 1900 some noted mathematicians published works developing geometry from its very beginning. They wanted to supplant approaches, based on Euclid’s, which han- dled some basic concepts awkwardly and imprecisely. They would introduce precision re- quired for generalization and application to new, delicate problems in higher mathematics. Their work was controversial: they departed from tradition, criticized standards of rigor, and addressed fundamental questions in philosophy. This paper follows the problem, Which geo- metric concepts are most elementary? It describes a false start, some successful solutions, and an argument that one of those is optimal. It’s about axioms, definitions, and definability, and emphasizes contributions of Mario Pieri (1860–1913) and Alfred Tarski (1901–1983). By fol- lowing this thread of ideas and personalities to the present, the author hopes to kindle interest in a fascinating research area and an exciting era in the history of mathematics. 1. INTRODUCTION. Around 1900 several noted mathematicians published major works on a subject familiar to us from school: developing geometry from the very beginning. They wanted to supplant the established approaches, which were based on Euclid’s, but which handled awkwardly and imprecisely some concepts that Euclid did not treat fully. They would present geometry with the precision required for general- ization and applications to new, delicate problems in higher mathematics—precision beyond the norm for most elementary classes. Work in this area was controversial: these mathematicians departed from tradition, criticized previous standards of rigor, and addressed fundamental questions in logic and philosophy of mathematics.2 After establishing background, this paper tells a story about research into the ques- tion, Which geometric concepts are most elementary? It describes a false start, some successful solutions, and a demonstration that one of those is in a sense optimal. -
What Is Neologicism?∗
What is Neologicism? 2 by Zermelo-Fraenkel set theory (ZF). Mathematics, on this view, is just applied set theory. Recently, ‘neologicism’ has emerged, claiming to be a successor to the ∗ What is Neologicism? original project. It was shown to be (relatively) consistent this time and is claimed to be based on logic, or at least logic with analytic truths added. Bernard Linsky Edward N. Zalta However, we argue that there are a variety of positions that might prop- erly be called ‘neologicism’, all of which are in the vicinity of logicism. University of Alberta Stanford University Our project in this paper is to chart this terrain and judge which forms of neologicism succeed and which come closest to the original logicist goals. As we look back at logicism, we shall see that its failure is no longer such a clear-cut matter, nor is it clear-cut that the view which replaced it (that 1. Introduction mathematics is applied set theory) is the proper way to conceive of math- ematics. We shall be arguing for a new version of neologicism, which is Logicism is a thesis about the foundations of mathematics, roughly, that embodied by what we call third-order non-modal object theory. We hope mathematics is derivable from logic alone. It is now widely accepted that to show that this theory offers a version of neologicism that most closely the thesis is false and that the logicist program of the early 20th cen- approximates the main goals of the original logicist program. tury was unsuccessful. Frege’s (1893/1903) system was inconsistent and In the positive view we put forward in what follows, we adopt the dis- the Whitehead and Russell (1910–13) system was not thought to be logic, tinctions drawn in Shapiro 2004, between metaphysical foundations for given its axioms of infinity, reducibility, and choice. -
Charles Sanders Peirce - Wikipedia, the Free Encyclopedia 9/2/10 4:55 PM
Charles Sanders Peirce - Wikipedia, the free encyclopedia 9/2/10 4:55 PM Charles Sanders Peirce From Wikipedia, the free encyclopedia Charles Sanders Peirce (pronounced /ˈpɜrs/ purse[1]) Charles Sanders Peirce (September 10, 1839 – April 19, 1914) was an American philosopher, logician, mathematician, and scientist, born in Cambridge, Massachusetts. Peirce was educated as a chemist and employed as a scientist for 30 years. It is largely his contributions to logic, mathematics, philosophy, and semiotics (and his founding of pragmatism) that are appreciated today. In 1934, the philosopher Paul Weiss called Peirce "the most original and versatile of American philosophers and America's greatest logician".[2] An innovator in many fields (including philosophy of science, epistemology, metaphysics, mathematics, statistics, research methodology, and the design of experiments in astronomy, geophysics, and psychology) Peirce considered himself a logician first and foremost. He made major contributions to logic, but logic for him encompassed much of that which is now called epistemology and philosophy of science. He saw logic as the Charles Sanders Peirce formal branch of semiotics, of which he is a founder. As early as 1886 he saw that logical operations could be carried out by Born September 10, 1839 electrical switching circuits, an idea used decades later to Cambridge, Massachusetts produce digital computers.[3] Died April 19, 1914 (aged 74) Milford, Pennsylvania Contents Nationality American 1 Life Fields Logic, Mathematics, 1.1 United States Coast Survey Statistics, Philosophy, 1.2 Johns Hopkins University Metrology, Chemistry 1.3 Poverty Religious Episcopal but 2 Reception 3 Works stance unconventional 4 Mathematics 4.1 Mathematics of logic C. -
Taboo Versus Axiom
TABOO VERSUS AXIOM KATUZI ONO Some important formal systems are really developable from a finite number of axioms in the lower classical predicate logic LK or in the intuitionistic predicate logic LJ. Any system of this kind can be developed in LK (or in LJ) from the single conjunction of all the axioms of the system. I have been intending to develop usual formal systems starting from TABOOS and standing on the primitive logic LO at first, since the logic too could be brought up to the usual logics by means of TABOOS in LOυ. In developing any formal system from TABOOS, we are forced to assume unwillingly that all the TABOOS are mutually equivalent, as far as we adopt more than one TABOOS for the system. If we could develop formal systems from single- TABOO TABOO-systems, we could get rid of this unwilling assumption. It would be well expected that any formal theory developable from a finite number of axioms in LK or in LJ would be developable from a single TABOO.2) In the present paper, I will prove that this is really the case. Before stating the theorem, let us define the δ-TRANSFORM Spy] of any sentence ® with respect to an h-ary relation £y (λ>0). SΓ&3 is introduced by a structural recursive definition as follows: @C8Qs (r)((©->g(r))->#(r)) for any elementary sentence ©, Received January 20, 1966. *> As for this plan, see Ono [1]. LO is called PRIMITIVE SYSTEM OF POSITIVE LOGIC in Ono [1]. The terminology PRIMITIVE LOGIC together with its reference notation LO has been introduced in Ono [2], 2) In my work [1], I had to assume this to bring up logics by means of TABOO systems. -
Mechanizing Induction
MECHANIZING INDUCTION Ronald Ortner and Hannes Leitgeb In this chapter we will deal with “mechanizing” induction, i.e. with ways in which theoretical computer science approaches inductive generalization. In the field of Machine Learning , algorithms for induction are developed. De- pending on the form of the available data, the nature of these algorithms may be very different. Some of them combine geometric and statistical ideas, while others use classical reasoning based on logical formalism. However, we are not so much interested in the algorithms themselves, but more on the philosophical and theoretical foundations they share. Thus in the first of two parts, we will examine different approaches and inductive assumptions in two particular learning settings. While many machine learning algorithms work well on a lot of tasks, the inter- pretation of the learned hypothesis is often difficult. Thus, while e.g. an algorithm surprisingly is able to determine the gender of the author of a given text with about 80 percent accuracy [Argamon and Shimoni, 2003 ], for a human it takes some extra effort to understand on the basis of which criteria the algorithm is able to do so. With that respect the advantage of approaches using logic are obvious: If the output hypothesis is a formula of predicate logic, it is easy to interpret. How- ever, if decision trees or algorithms from the area of inductive logic programming are based purely on classical logic, they suffer from the fact that most universal statements do not hold for exceptional cases, and classical logic does not offer any convenient way of representing statements which are meant to hold in the “normal case”.