Kurt Gödel and the Foundations of Mathematics
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Game Dynamics Karl Sigmund University of Vienna, Austria
The Center for Control, Dynamical Systems, and Computation University of California at Santa Barbara Winter 2007 Seminar Series Presents Game Dynamics Karl Sigmund University of Vienna, Austria Tuesday, February 13th, 2007 2:00pm-4:00pm ESB 1001 Abstract: Game dynamics can be viewed as a combination of game theory and ecology, with applications in many other fields. In this talk, the role of heteroclinic attractors (consisting of saddle points and saddle connections) will be highlighted. In usual dynamical systems, such attractors are not robust, but they often occur (in the form of Rock-Paper-Scissors cycles) in strategic interactions. This talk deals with examples, basic results and open problems. About the Speaker: Karl Sigmund attended school in the lycée francais de Vienne. From 1963 to 1968, he studied at the Institute of Mathematics at the University of Vienna, and obtained his Ph.D. under the supervision of Leopold Schmetterer. He then spent the following postdoc years in Manchester (68-69), the Institut des Hautes Etudes in Bures sur Yvette near Paris (69-70), the Hebrew University in Jerusalem (1970- 71), the University of Vienna (1971-72) and the Austrian Academy of Science (1972-73). In 1973 Karl was appointed C3-professor at the University of Göttingen, and in 1974 full professor at the Institute of Mathematics in Vienna. His main scientific interest during these years was in ergodic theory and dynamical systems. From 1977 on, Karl became increasingly interested in different fields of biomathematics, and collaborated with Peter Schuster and Josef Hofbauer on mathematical ecology, chemical kinetics and population genetics, but especially on the new field of evolutionary game dynamics and replicator equations. -
* Supplied by EMS Are the Best That Can Be Made from the Original
DOCUMENT RESUME ED 115 128 FL 007 330 AUTHOR Thogmartin, Clyde TITLE A Bibliography of Empirical Investigations of Certain Aspects of Foreign Language Teaching and Learning, 1925-1975. PUB DATE 75 NOTE 67p. EDRS PRICE MF-$0.76 HC-$3.32 Plus Postage DESCRIPTORS Academic Achievement; *Bibliographies; Bilingual Education; Bilingualism; Educational Equipment; *Educational Research; Error Patterns; Fles; Individual Differences; Instructional Materials; Instructional Media; Interference (Language Learning); *Language Instruction; Language Proficiency; *Language Research; Language Skills; Language Tests; Psycholinguistics; *Second Language Learning; Student Attitudes; Teaching Methods; Transfer of Training; Vocabulary Development ABSTRACT This 647-item bibliography is limited to reports on empirical research and discussions of research reports on various aspects of foreign language learning, mostly drawn from American and British journals and Ph.D. dissertations since 1925 and from ERIC documents. Principal topics include content of teaching materials, cognitive effects of bilingualism, measurement of bilingual proficiency, psychological studies of bilinguals, relationships between various language skills, the psycholinguistics of second language learning, transfer and interference, error analysis, vocabulary learning, bilingual education, foreign languages in the elementary schools, individual differences in language learning success, prognosis, teaching methods, equipment, media, testing, language difficulty, and effects of language learning -
A Decade of Lattice Cryptography
Full text available at: http://dx.doi.org/10.1561/0400000074 A Decade of Lattice Cryptography Chris Peikert Computer Science and Engineering University of Michigan, United States Boston — Delft Full text available at: http://dx.doi.org/10.1561/0400000074 Foundations and Trends R in Theoretical Computer Science Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 United States Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 The preferred citation for this publication is C. Peikert. A Decade of Lattice Cryptography. Foundations and Trends R in Theoretical Computer Science, vol. 10, no. 4, pp. 283–424, 2014. R This Foundations and Trends issue was typeset in LATEX using a class file designed by Neal Parikh. Printed on acid-free paper. ISBN: 978-1-68083-113-9 c 2016 C. Peikert All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, photocopying, recording or otherwise, without prior written permission of the publishers. Photocopying. In the USA: This journal is registered at the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923. Authorization to photocopy items for in- ternal or personal use, or the internal or personal use of specific clients, is granted by now Publishers Inc for users registered with the Copyright Clearance Center (CCC). The ‘services’ for users can be found on the internet at: www.copyright.com For those organizations that have been granted a photocopy license, a separate system of payment has been arranged. -
The Best Nurturers in Computer Science Research
The Best Nurturers in Computer Science Research Bharath Kumar M. Y. N. Srikant IISc-CSA-TR-2004-10 http://archive.csa.iisc.ernet.in/TR/2004/10/ Computer Science and Automation Indian Institute of Science, India October 2004 The Best Nurturers in Computer Science Research Bharath Kumar M.∗ Y. N. Srikant† Abstract The paper presents a heuristic for mining nurturers in temporally organized collaboration networks: people who facilitate the growth and success of the young ones. Specifically, this heuristic is applied to the computer science bibliographic data to find the best nurturers in computer science research. The measure of success is parameterized, and the paper demonstrates experiments and results with publication count and citations as success metrics. Rather than just the nurturer’s success, the heuristic captures the influence he has had in the indepen- dent success of the relatively young in the network. These results can hence be a useful resource to graduate students and post-doctoral can- didates. The heuristic is extended to accurately yield ranked nurturers inside a particular time period. Interestingly, there is a recognizable deviation between the rankings of the most successful researchers and the best nurturers, which although is obvious from a social perspective has not been statistically demonstrated. Keywords: Social Network Analysis, Bibliometrics, Temporal Data Mining. 1 Introduction Consider a student Arjun, who has finished his under-graduate degree in Computer Science, and is seeking a PhD degree followed by a successful career in Computer Science research. How does he choose his research advisor? He has the following options with him: 1. Look up the rankings of various universities [1], and apply to any “rea- sonably good” professor in any of the top universities. -
Constraint Based Dimension Correlation and Distance
Preface The papers in this volume were presented at the Fourteenth Annual IEEE Conference on Computational Complexity held from May 4-6, 1999 in Atlanta, Georgia, in conjunction with the Federated Computing Research Conference. This conference was sponsored by the IEEE Computer Society Technical Committee on Mathematical Foundations of Computing, in cooperation with the ACM SIGACT (The special interest group on Algorithms and Complexity Theory) and EATCS (The European Association for Theoretical Computer Science). The call for papers sought original research papers in all areas of computational complexity. A total of 70 papers were submitted for consideration of which 28 papers were accepted for the conference and for inclusion in these proceedings. Six of these papers were accepted to a joint STOC/Complexity session. For these papers the full conference paper appears in the STOC proceedings and a one-page summary appears in these proceedings. The program committee invited two distinguished researchers in computational complexity - Avi Wigderson and Jin-Yi Cai - to present invited talks. These proceedings contain survey articles based on their talks. The program committee thanks Pradyut Shah and Marcus Schaefer for their organizational and computer help, Steve Tate and the SIGACT Electronic Publishing Board for the use and help of the electronic submissions server, Peter Shor and Mike Saks for the electronic conference meeting software and Danielle Martin of the IEEE for editing this volume. The committee would also like to thank the following people for their help in reviewing the papers: E. Allender, V. Arvind, M. Ajtai, A. Ambainis, G. Barequet, S. Baumer, A. Berthiaume, S. -
Interactions of Computational Complexity Theory and Mathematics
Interactions of Computational Complexity Theory and Mathematics Avi Wigderson October 22, 2017 Abstract [This paper is a (self contained) chapter in a new book on computational complexity theory, called Mathematics and Computation, whose draft is available at https://www.math.ias.edu/avi/book]. We survey some concrete interaction areas between computational complexity theory and different fields of mathematics. We hope to demonstrate here that hardly any area of modern mathematics is untouched by the computational connection (which in some cases is completely natural and in others may seem quite surprising). In my view, the breadth, depth, beauty and novelty of these connections is inspiring, and speaks to a great potential of future interactions (which indeed, are quickly expanding). We aim for variety. We give short, simple descriptions (without proofs or much technical detail) of ideas, motivations, results and connections; this will hopefully entice the reader to dig deeper. Each vignette focuses only on a single topic within a large mathematical filed. We cover the following: • Number Theory: Primality testing • Combinatorial Geometry: Point-line incidences • Operator Theory: The Kadison-Singer problem • Metric Geometry: Distortion of embeddings • Group Theory: Generation and random generation • Statistical Physics: Monte-Carlo Markov chains • Analysis and Probability: Noise stability • Lattice Theory: Short vectors • Invariant Theory: Actions on matrix tuples 1 1 introduction The Theory of Computation (ToC) lays out the mathematical foundations of computer science. I am often asked if ToC is a branch of Mathematics, or of Computer Science. The answer is easy: it is clearly both (and in fact, much more). Ever since Turing's 1936 definition of the Turing machine, we have had a formal mathematical model of computation that enables the rigorous mathematical study of computational tasks, algorithms to solve them, and the resources these require. -
Psychology of School Learning: Views of the Learner
DOCUMENT RESUME ED 104 859 SP 009 097 AUTHOR Bart, William M., Ed.; Wong, Martin R., Ed. TITLE Psychology of School Learning: Views of the Learner. Volume I: Environmentalism. INSTITUTION MSS Information Ccrp., New York, N.Y. PUB DATE 74 'NOTE 249p. AVAILABLE FROM MSS Information 'orporation, 655 Madison Avenue, New York, New York 10021 ($6.25 paper, $12.00 cloth, 20 percent discount on orders of $200.00 or more) EDRS PRICE MF-$0.76 HC-$12.05 PLUS POSTAGE DESCRIPTORS Behavioral Objectives; Computer Assisted Instruction; Educational Philosophy; *Educational Psychology; *Environmental Influences; Higher Education; *Learning; *Learning Specialists; Reinforcement; Teacher Education ABSTRACT This document is the first of three volumes presenting essays from three schools of thought regarding learning. Volume one consists of readings from psychologists, philosophers, and learning theorists concerning the view that the learner isa product primarily of environmental factors. The list of essays includes the following:(a) "Ideas and Their Origin," (b) "The Free and Happy Student," (c) "The Technology of Teaching," (d) "Treatment of Nonreading in a Culturally Deprived Juvenile Delinquent: An Application of Reinforcement Principles," (e) "Production and Elimination of Disruptive Classroom Behavior by Systematically Varying Teacher's Behavior," (f) "Learning Theory Approaches to Classroom Management: Rationale and Intervention Techniques," (g) "A Token Reinforcement Program in a Public School: A Replication and Systematic Analysis," (h) "Educational -
Commemorative Meeting for Alfred Tarski Stanford University-November 7, 1983
Patrick Suppes received his Ph.D. in Philosophy in 1950 at Columbia Univer sity, where he worked with Ernest Nagel. He has been at Stanford since 1950 and is now Professor ofPhilosophy and Statistics. Suppes' main research inter ests include the philosophy of science, theory of measurement, decision theory and probability, and computer-assisted education. He is a member of the Na tional Academy of Sciences. Jon Barwise received his Ph.D. in Mathematics in 1967 at Stanford University, where he .worked with Solomon Feferman. After teaching at U.C.L.A., Yale, and Wisconsin, he returned to Stanford as Professor of Philosophy in 1983. Barwise's main research interests include mathematical logic, especially model theory, set theory, and generalized re cursion theory; and applications of logic to the semantics of natural language. At Stanford, Barwise has been Director of the Center for Study of Language and Information, and is currently chairman of the Program in Symbolic Sys tems. Solomon Feferman received his Ph.D. in Mathematics in 1957 at the University of California, Berkeley, where he studied with Alfred Tarski. He has been at Stanford since 1956, where he is Professor of Mathematics and Phi losophy. His research interests are in mathematical logic and the foundations of mathematics, especially proof theory and constructive and semiconstructive mathematics, as well as in the history of modern logic. Feferman is Editor-in Chief of the Collected Works of Kurt Godel; he is currently Chairman of the Department of Mathematics. Commemorative Meeting for Alfred Tarski Stanford University-November 7, 1983 PATRICK SUPPES, JON BARWISE, AND SOLOMON FEFERMAN, SPEAKERS INTRODUCTION The meeting was held in memory of Professor Alfred Tarski, who died at the age of 82 on October 28, 1983. -
Optimal Hitting Sets for Combinatorial Shapes
Optimal Hitting Sets for Combinatorial Shapes Aditya Bhaskara∗ Devendra Desai† Srikanth Srinivasan‡ November 5, 2018 Abstract We consider the problem of constructing explicit Hitting sets for Combinatorial Shapes, a class of statistical tests first studied by Gopalan, Meka, Reingold, and Zuckerman (STOC 2011). These generalize many well-studied classes of tests, including symmetric functions and combi- natorial rectangles. Generalizing results of Linial, Luby, Saks, and Zuckerman (Combinatorica 1997) and Rabani and Shpilka (SICOMP 2010), we construct hitting sets for Combinatorial Shapes of size polynomial in the alphabet, dimension, and the inverse of the error parame- ter. This is optimal up to polynomial factors. The best previous hitting sets came from the Pseudorandom Generator construction of Gopalan et al., and in particular had size that was quasipolynomial in the inverse of the error parameter. Our construction builds on natural variants of the constructions of Linial et al. and Rabani and Shpilka. In the process, we construct fractional perfect hash families and hitting sets for combinatorial rectangles with stronger guarantees. These might be of independent interest. 1 Introduction Randomness is a tool of great importance in Computer Science and combinatorics. The probabilistic method is highly effective both in the design of simple and efficient algorithms and in demonstrating the existence of combinatorial objects with interesting properties. But the use of randomness also comes with some disadvantages. In the setting of algorithms, introducing randomness adds to the number of resource requirements of the algorithm, since truly random bits are hard to come by. For combinatorial constructions, ‘explicit’ versions of these objects often turn out to have more structure, which yields advantages beyond the mere fact of their existence (e.g., we know of explicit arXiv:1211.3439v1 [cs.CC] 14 Nov 2012 error-correcting codes that can be efficiently encoded and decoded, but we don’t know if random codes can [5]). -
Exhibition: the Vienna Circle - Exact Thinking in Demented Times
! ! Exhibition: The Vienna Circle - Exact Thinking In Demented Times. As part of the 650 year anniversary of the University of Vienna, the exhibition „The Vienna Circle“ will be displayed at the University’s main building from May 20th, 2015 until October 31st, 2015. The Vienna Circle, a group of outstanding thinkers, played an important part in Philosophy and science in the 1920’s and 1930’s: The group’s discussions and philosophical approaches set the cornerstones for important developments in a multitude of fields of science. On Tuesday, May 19th, at 5:00pm the exhibition will be opened by the rector of the University Vienna Heinz W. Engl. Other distinguished speakers include major Michael Häupl, the president of the Austrian Academy of Science Anton Zeilinger, Nobel Prize Winner Martin Karplus as well as Media Artist Peter Weibel. The exhibition was curated by Karl Sigmund and Friedrich Stadler. After leaving Vienna, the exhibition will be displayed in Karlsruhe. „Today, the Vienna Circle would be considered an internationally influential science Think Tank. Its members stood for the free development of science, scientific and rational analysis in politics and culture as well as the modernization of the society they lived in. The achievements of the members of the Vienna Circle still have impact on today’s science and research areas: the discussions of the Vienna Circle eventually led to innovations like the basics of mathematical logic as well as theoretical computer science“, says Heinz W. Engl, rector of the University of Vienna. The objects and documents mostly focus on the philosophical questions the Vienna Circle discussed: How can the efficiency of mathematics be explained? What is the role of logical propositions? What is the basis of scientific knowledge? The greatest challenge for the curators was to „visualize philosophy“: making the abstract, philosophical work of the Vienna Circle accessible to and understandable for a broad audience. -
Science Lives: Video Portraits of Great Mathematicians
Science Lives: Video Portraits of Great Mathematicians accompanied by narrative profiles written by noted In mathematics, beauty is a very impor- mathematics biographers. tant ingredient… The aim of a math- Hugo Rossi, director of the Science Lives project, ematician is to encapsulate as much as said that the first criterion for choosing a person you possibly can in small packages—a to profile is the significance of his or her contribu- high density of truth per unit word. tions in “creating new pathways in mathematics, And beauty is a criterion. If you’ve got a theoretical physics, and computer science.” A beautiful result, it means you’ve got an secondary criterion is an engaging personality. awful lot identified in a small compass. With two exceptions (Atiyah and Isadore Singer), the Science Lives videos are not interviews; rather, —Michael Atiyah they are conversations between the subject of the video and a “listener”, typically a close friend or colleague who is knowledgeable about the sub- Hearing Michael Atiyah discuss the role of beauty ject’s impact in mathematics. The listener works in mathematics is akin to reading Euclid in the together with Rossi and the person being profiled original: You are going straight to the source. The to develop a list of topics and a suggested order in quotation above is taken from a video of Atiyah which they might be discussed. “But, as is the case made available on the Web through the Science with all conversations, there usually is a significant Lives project of the Simons Foundation. Science amount of wandering in and out of interconnected Lives aims to build an archive of information topics, which is desirable,” said Rossi. -
14 Patrick Suppes
14 Patrick Suppes Lucie Stern Professor of Philosophy, Emeritus Stanford University, USA 1. Why were you initially drawn to computational or in formational issues? I begin with some history. I am not sure just when I first thought about the use of computers for computation, but I do remember the late 1950s when Dick Atkinson and I were writing a book on applications of learning models and stimulus-response reinforce ment concepts to simple game situations. The book is full of ex tended computations supported by use of the I.B.M. 650 Com puter at Stanford, which was one of the very earliest made avail able to academic communities to have the possibility of going be yond the old days of computing with hand calculators. We say this in the preface of Suppes and Atkinson (1960): "Evan Linick has been indispensable in programming many problems for the I.B.M. 650 Computer at Stanford; we are also indebted to Richard Hill of the Western Data Processing Center for his cooperation." This brief acknowledgement is all we had to say about what was really a first, big-time, move into computing from my own standpoint. At that time, the only task was facilitating the many statistical estimates of parameters and the like for the models introduced in the book. It is important to realize how fundamental the change was in feasible applications of statistics with the introduction of digital computers in the 1950s. Even very simple formulations of linear-programming or linear-regression problems, that were prac tically unsolvable, could now be used to address all kinds of inter esting questions in theories of behavior and social interaction.