Nonstandard Models of Arithmetic and Set Theory

Nonstandard Models of Arithmetic and Set Theory

Author: Ali Enayat

Publisher: American Mathematical Soc.

Published: 2004

Total Pages: 184

ISBN-13: 0821835351

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This is the proceedings of the AMS special session on nonstandard models of arithmetic and set theory held at the Joint Mathematics Meetings in Baltimore (MD). The volume opens with an essay from Haim Gaifman that probes the concept of non-standardness in mathematics and provides a fascinating mix of historical and philosophical insights into the nature of nonstandard mathematical structures. In particular, Gaifman compares and contrasts the discovery of nonstandard models with other key mathematical innovations, such as the introduction of various number systems, the modern concept of function, and non-Euclidean geometries. Other articles in the book present results related to nonstandard models in arithmetic and set theory, including a survey of known results on the Turing upper bounds of arithmetic sets and functions. The volume is suitable for graduate students and research mathematicians interested in logic, especially model theory.


Models of Peano Arithmetic

Models of Peano Arithmetic

Author: Richard Kaye

Publisher:

Published: 1991

Total Pages: 312

ISBN-13:

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Non-standard models of arithmetic are of interest to mathematicians through the presence of infinite integers and the various properties they inherit from the finite integers. Since their introduction in the 1930s, they have come to play an important role in model theory, and in combinatorics through independence results such as the Paris-Harrington theorem. This book is an introduction to these developments, and stresses the interplay between the first-order theory, recursion-theoretic aspects, and the structural properties of these models. Prerequisites for an understanding of the text have been kept to a minimum, these being a basic grounding in elementary model theory and a familiarity with the notions of recursive, primitive recursive, and r.e. sets. Consequently, the book is suitable for postgraduate students coming to the subject for the first time, and a number of exercises of varying degrees of difficulty will help to further the reader's understanding.


Model Theory in Algebra, Analysis and Arithmetic

Model Theory in Algebra, Analysis and Arithmetic

Author: Lou van den Dries

Publisher: Springer

Published: 2014-09-20

Total Pages: 201

ISBN-13: 3642549365

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Presenting recent developments and applications, the book focuses on four main topics in current model theory: 1) the model theory of valued fields; 2) undecidability in arithmetic; 3) NIP theories; and 4) the model theory of real and complex exponentiation. Young researchers in model theory will particularly benefit from the book, as will more senior researchers in other branches of mathematics.


An Introduction to Ramsey Theory

An Introduction to Ramsey Theory

Author: Matthew Katz

Publisher: American Mathematical Soc.

Published: 2018-10-03

Total Pages: 224

ISBN-13: 1470442906

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This book takes the reader on a journey through Ramsey theory, from graph theory and combinatorics to set theory to logic and metamathematics. Written in an informal style with few requisites, it develops two basic principles of Ramsey theory: many combinatorial properties persist under partitions, but to witness this persistence, one has to start with very large objects. The interplay between those two principles not only produces beautiful theorems but also touches the very foundations of mathematics. In the course of this book, the reader will learn about both aspects. Among the topics explored are Ramsey's theorem for graphs and hypergraphs, van der Waerden's theorem on arithmetic progressions, infinite ordinals and cardinals, fast growing functions, logic and provability, Gödel incompleteness, and the Paris-Harrington theorem. Quoting from the book, “There seems to be a murky abyss lurking at the bottom of mathematics. While in many ways we cannot hope to reach solid ground, mathematicians have built impressive ladders that let us explore the depths of this abyss and marvel at the limits and at the power of mathematical reasoning at the same time. Ramsey theory is one of those ladders.”


Predicative Arithmetic. (MN-32)

Predicative Arithmetic. (MN-32)

Author: Edward Nelson

Publisher: Princeton University Press

Published: 2014-07-14

Total Pages: 199

ISBN-13: 1400858925

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This book develops arithmetic without the induction principle, working in theories that are interpretable in Raphael Robinson's theory Q. Certain inductive formulas, the bounded ones, are interpretable in Q. A mathematically strong, but logically very weak, predicative arithmetic is constructed. Originally published in 1986. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.


Mathematics for Machine Learning

Mathematics for Machine Learning

Author: Marc Peter Deisenroth

Publisher: Cambridge University Press

Published: 2020-04-23

Total Pages: 392

ISBN-13: 1108569323

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The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.


Mathematical Logic and Model Theory

Mathematical Logic and Model Theory

Author: Alexander Prestel

Publisher: Springer Science & Business Media

Published: 2011-08-21

Total Pages: 198

ISBN-13: 1447121767

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Mathematical Logic and Model Theory: A Brief Introduction offers a streamlined yet easy-to-read introduction to mathematical logic and basic model theory. It presents, in a self-contained manner, the essential aspects of model theory needed to understand model theoretic algebra. As a profound application of model theory in algebra, the last part of this book develops a complete proof of Ax and Kochen's work on Artin's conjecture about Diophantine properties of p-adic number fields. The character of model theoretic constructions and results differ quite significantly from that commonly found in algebra, by the treatment of formulae as mathematical objects. It is therefore indispensable to first become familiar with the problems and methods of mathematical logic. Therefore, the text is divided into three parts: an introduction into mathematical logic (Chapter 1), model theory (Chapters 2 and 3), and the model theoretic treatment of several algebraic theories (Chapter 4). This book will be of interest to both advanced undergraduate and graduate students studying model theory and its applications to algebra. It may also be used for self-study.


Subsystems of Second Order Arithmetic

Subsystems of Second Order Arithmetic

Author: Stephen George Simpson

Publisher: Cambridge University Press

Published: 2009-05-29

Total Pages: 461

ISBN-13: 052188439X

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This volume examines appropriate axioms for mathematics to prove particular theorems in core areas.


Useless Arithmetic

Useless Arithmetic

Author: Orrin H. Pilkey

Publisher: Columbia University Press

Published: 2007-01-09

Total Pages: 397

ISBN-13: 0231506996

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Noted coastal geologist Orrin Pilkey and environmental scientist Linda Pilkey-Jarvis show that the quantitative mathematical models policy makers and government administrators use to form environmental policies are seriously flawed. Based on unrealistic and sometimes false assumptions, these models often yield answers that support unwise policies. Writing for the general, nonmathematician reader and using examples from throughout the environmental sciences, Pilkey and Pilkey-Jarvis show how unquestioned faith in mathematical models can blind us to the hard data and sound judgment of experienced scientific fieldwork. They begin with a riveting account of the extinction of the North Atlantic cod on the Grand Banks of Canada. Next they engage in a general discussion of the limitations of many models across a broad array of crucial environmental subjects. The book offers fascinating case studies depicting how the seductiveness of quantitative models has led to unmanageable nuclear waste disposal practices, poisoned mining sites, unjustifiable faith in predicted sea level rise rates, bad predictions of future shoreline erosion rates, overoptimistic cost estimates of artificial beaches, and a host of other thorny problems. The authors demonstrate how many modelers have been reckless, employing fudge factors to assure "correct" answers and caring little if their models actually worked. A timely and urgent book written in an engaging style, Useless Arithmetic evaluates the assumptions behind models, the nature of the field data, and the dialogue between modelers and their "customers."


Modeling, Design, and Simulation of Systems with Uncertainties

Modeling, Design, and Simulation of Systems with Uncertainties

Author: Andreas Rauh

Publisher: Springer Science & Business Media

Published: 2011-06-06

Total Pages: 356

ISBN-13: 3642159567

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To describe the true behavior of most real-world systems with sufficient accuracy, engineers have to overcome difficulties arising from their lack of knowledge about certain parts of a process or from the impossibility of characterizing it with absolute certainty. Depending on the application at hand, uncertainties in modeling and measurements can be represented in different ways. For example, bounded uncertainties can be described by intervals, affine forms or general polynomial enclosures such as Taylor models, whereas stochastic uncertainties can be characterized in the form of a distribution described, for example, by the mean value, the standard deviation and higher-order moments. The goal of this Special Volume on Modeling, Design, and Simulation of Systems with Uncertainties is to cover modern methods for dealing with the challenges presented by imprecise or unavailable information. All contributions tackle the topic from the point of view of control, state and parameter estimation, optimization and simulation. Thematically, this volume can be divided into two parts. In the first we present works highlighting the theoretic background and current research on algorithmic approaches in the field of uncertainty handling, together with their reliable software implementation. The second part is concerned with real-life application scenarios from various areas including but not limited to mechatronics, robotics, and biomedical engineering.