Series Y Largometrajes Como Recurso Didáctico En Matemáticas En

Total Page:16

File Type:pdf, Size:1020Kb

Series Y Largometrajes Como Recurso Didáctico En Matemáticas En TESISDOCTORAL 2 0 1 5 SERIESYLARGOMETRAJESCOMORECURSODIDÁCTICOEN MATEMÁTICASENEDUCACIÓNSECUNDARIA pablo beltrán pellicer Ingeniero de Telecomunicación por la Universidad de Zaragoza Máster en Tecnologías de la Información y Comunicaciones en Redes Móviles e Inalámbricas por la Universidad de Zaragoza Máster en Innovación e Investigación en Educación por la UNED. departamento de didáctica, organización escolar y didácticas especiales Facultad de Educación Dirección de la tesis: dr. antonio medina rivilla Codirección: dra. mercedes quero gervilla departamento de didáctica, organización escolar y didácticas especiales Facultad de Educación SERIESYLARGOMETRAJESCOMORECURSODIDÁCTICOEN MATEMÁTICASENEDUCACIÓNSECUNDARIA pablo beltrán pellicer Ingeniero de Telecomunicación por la Universidad de Zaragoza Máster en Tecnologías de la Información y Comunicaciones en Redes Móviles e Inalámbricas por la Universidad de Zaragoza Máster en Innovación e Investigación en Educación por la UNED. Dirección de la tesis: dr. antonio medina rivilla Codirección: dra. mercedes quero gervilla A Sara, Arturo y Alonso, mi luna y estrellas. Gracias por quererme a pesar del tiempo robado. AGRADECIMIENTOS El germen de esta tesis hay que buscarlo en mi trabajo fin de máster, que realicé bajo la tutela de Isabel Escudero. Ella me animó a continuar y comenzó a dirigirme. Poco después, y debido a avatares de la vida, Isabel tuvo que apartarse de este proyecto. No sé si el resultado final es el que ella imaginaba, pero lo justo es agradecerle aquí la confianza que depositó en mí. En aquellos titubeantes primeros pasos, Mercedes Quero asumió la codirección con Isabel. El agradecimiento para ella es doble. Por un lado, sus consejos y orientaciones a la hora de estructurar la investigación y el documento final han sido siempre certe- ros y necesarios. Sus palabras fueron en todo momento palabras de aliento. Por otra parte, Mercedes actuó como un auténtico nexo de unión, allanando el camino para que Antonio Medina dirigiera la tesis hasta el final. Para Antonio, siempre atento y disponible, solamente tengo elogios. Este humilde trabajo no habría sido lo mismo de no haber contado con su dilatada experiencia y espectacular bagaje académico. Todo ello, unido a que Antonio es un torrente de ideas, me ha permitido aprender lo inimaginable, creciendo como profesor y como investigador. Por ello, desde estas líneas le digo gracias. Pero sobre todo, por el valor que demostró al tomar el timón de un barco que ya había zarpado. Mientras desarrollaba el trabajo fin de máster, tuve la ocasión de entrevistar a José Mª Sorando, uno de los pioneros en utilizar fragmentos de cine y series en clase de Matemáticas, y cuyas referencias salpican el texto de la tesis. La inspiración que me produjo aquella charla todavía persiste a día de hoy. Después de leer los primeros textos sobre la teoría de las situaciones didácticas, me asaltaron una serie de inquietudes que me hicieron ponerme en contacto con investi- iv gadores expertos en la materia. Aunque el marco teórico que he terminado utilizando ha variado bastante desde aquellos compases iniciales, nunca olvidaré los correos de Nicholas Balacheff ni la charla telefónica con Pilar Orús. Espero que sus consejos se noten en la filosofía seguida en el diseño de las secuencias didácticas. El proyecto eTwinning nunca habría sido lo mismo de no haber conocido a Anna Asti. Su implicación e ilusión fueron un acicate para mi investigación. Agradezco sinceramente las opiniones de Antonio F. Costa, Ángel Requena y Al- fonso J. Población, así como a los expertos que participaron en la evaluación del cues- tionario piloto de las fase avanzada, Miguel Ángel García, Lamberto López y Jaime Martínez. Carlos y María jugaron un papel fundamental en el desarrollo de la investigación, prestándose a poner en práctica las secuencias didácticas y recoger los datos de los mapas de humor, así como de los cuestionarios de los alumnos. Hacen falta más pro- fesores como ellos. En la elección de los mapas auto-organizados como herramienta de análisis, ha tenido mucho que ver el que ya la hubiera empleado en mi proyecto fin de carrera. Agradezco desde estas líneas al que fuera mi director entonces, David Buldain, que me hizo ver todo el potencial que tenían. Cada vez que he hablado con Ana Gascón sobre la tesis, al día siguiente me encon- traba con un correo lleno de sugerencias. Gracias Ana. Por último, debo añadir que cualquier investigador sabrá que no es fácil compaginar el trabajo que conlleva una tesis con la vida familiar y laboral. En mi caso, no tengo duda de que ha requerido de altas dosis de comprensión y de ayuda por parte de mi entorno cercano. No tengo palabras para ellos. En definitiva, a todos que han hecho posible que llegara hasta aquí. Ha sido mucho tiempo dedicado a ella y seguramente me olvide de nombrar a alguien. Espero que sepan perdonarme. v ÍNDICEGENERAL Acrónimos xi Índice de figuras xii Índice de tablas xviii i introducción 1 1 introducción 3 1.1 Justificación y oportunidad 3 1.2 Objeto de estudio 6 1.3 Preguntas de investigación y objetivos 8 1.3.1 Preguntas de investigación 8 1.3.2 Objetivos 9 1.4 Metodología 10 1.5 Estructura de la tesis 12 ii marco teórico 15 2 estudios previos sobre matemáticas en el cine y su utilización didáctica 17 2.1 Una reflexión inicial 17 2.2 Estudios sobre aplicaciones didácticas del cine en Matemáticas 19 2.3 Estudios sobre referencias matemáticas en el cine y las series 24 2.3.1 Páginas web 24 2.3.2 Artículos y libros 33 2.4 Estudios sobre el papel del contexto en Matemáticas 36 2.4.1 Educación matemática realista 36 2.4.2 El cine como contexto 43 3 marco conceptual 49 3.1 Enfoque ontosemiótico 50 vi índice general vii 3.1.1 Valoración de la idoneidad didáctica de un proceso de enseñanza- aprendizaje 51 3.2 Ingeniería didáctica: fases de un estudio EOS 55 3.2.1 Análisis preliminares 57 3.2.2 Análisis a priori y diseño de las secuencias de clase 58 3.2.3 Experimentación 58 3.2.4 Análisis a posteriori y validación 59 3.3 Recogida de información emocional: mapas de humor 59 3.4 Análisis de datos: mapas auto-organizados 66 3.4.1 Fundamentos de los mapas auto-organizados 71 3.4.2 Visualizaciones de los mapas y Java SOMToolbox 75 4 implicaciones didácticas 79 4.1 Clasificaciones de fragmentos de películas o series 81 4.2 Diversidad de contextos 87 iii diseño de secuencias didácticas 89 5 modelo de diseño y análisis de las secuencias didácticas 91 5.1 Modelo de diseño 91 5.2 Modelo de análisis 94 5.2.1 Estudio de la idoneidad didáctica 94 5.2.2 Idoneidad epistémica 96 5.2.3 Idoneidad cognitiva 96 5.2.4 Idoneidad interaccional 97 5.2.5 Idoneidad mediacional 98 5.2.6 Idoneidad afectiva 99 5.2.7 Idoneidad ecológica 101 6 secuencias didácticas y sus análisis a priori 103 6.1 Bloque de números 104 6.1.1 Contact: números primos 104 6.1.2 Blackjack: porcentajes (descuentos) 115 6.1.3 Granujas de medio pelo: fracciones 126 6.1.4 Los Simpson: fracciones (total sabiendo una parte) 133 viii índice general 6.1.5 Futurama: fracciones (intereses) 140 6.2 Bloque de álgebra 148 6.2.1 Cielo de octubre: ecuaciones de 2º grado 148 6.2.2 Jungla de Cristal III: ecuaciones, resolución de problemas 161 6.2.3 The Big Bang Theory: valor numérico 172 6.2.4 Los Simpson: ecuaciones de segundo grado 183 6.2.5 La vida es bella y Los caballeros de la mesa cuadrada: enuncia- dos engañosos 191 6.3 Bloque de funciones y gráficas 203 6.3.1 Los Simpson Inteligencia vs Felicidad 203 6.3.2 Pandorum - Crecimiento de la población 211 6.4 Bloque de geometría 218 6.4.1 Annapolis: ángulos 218 6.4.2 Numb3rs: volumen 225 6.4.3 El mago de Oz, teorema de Pitágoras 234 6.4.4 Apollo XIII, ángulos 241 6.5 Bloque de probabilidad y estadística 248 6.5.1 Moneyball: estadística 248 6.5.2 Numb3rs, episodio piloto: experimentos aleatorios 259 6.6 Conclusiones de los análisis a priori 266 iv trabajo de campo 275 7 planteamiento del trabajo de campo 277 8 fase inicial 283 8.1 Descripción general del trabajo en la fase inicial 283 8.1.1 Enfoque de investigación 283 8.1.2 Muestra 284 8.1.3 Instrumentos 285 8.2 Objetivos y estructura del proyecto 285 8.3 Desarrollo del proyecto 288 8.3.1 Trabajo con escenas: Jungla de cristal III 288 8.3.2 Trabajo con escenas: Granujas de medio pelo 291 índice general ix 8.4 Evaluación final y resultados 293 8.4.1 Cuestionario final para los alumnos 295 8.5 Conclusiones de la fase inicial 298 9 fase avanzada 301 9.1 Descripción general del trabajo 301 9.1.1 Enfoque de la investigación en la fase avanzada 301 9.1.2 Muestra del estudio 302 9.1.3 Instrumentos de investigación 303 9.2 Cuestionario inicial 306 9.2.1 Descripción 306 9.2.2 Muestra para el cuestionario 307 9.2.3 Elaboración del cuestionario 307 9.2.4 Análisis estadístico descriptivo global 312 9.2.5 Conclusiones del cuestionario inicial 332 9.3 Recogida y análisis de la información 334 9.3.1 Mapas de humor 334 9.3.2 Análisis de la idoneidad emocional con mapas auto-organizados 336 9.4 Análisis de los grupos 343 9.4.1 Grupo 1 343 9.4.2 Grupo 2 371 9.4.3 Conclusiones de los análisis con SOM 396 v conclusión 399 10 conclusiones de la tesis 401 11 líneas futuras de investigación 409 11.1 Diseño de procesos de enseñanza-aprendizaje 409 11.2 Desarrollo de herramientas online 410 11.3 Mapas auto-organizados condicionados 410 Referencias 413 Referencias a películas y series de ficción 421 x índice general vi apéndices 423 a cuestionario de la fase avanzada 425 b currículo oficial de 2º de eso 469 b.1 Contenidos comunes 469 b.2 Bloque de números 471 b.3 Bloque de álgebra 474 b.4 Bloque de geometría 475
Recommended publications
  • 5.2 Intractable Problems -- NP Problems
    Algorithms for Data Processing Lecture VIII: Intractable Problems–NP Problems Alessandro Artale Free University of Bozen-Bolzano [email protected] of Computer Science http://www.inf.unibz.it/˜artale 2019/20 – First Semester MSc in Computational Data Science — UNIBZ Some material (text, figures) displayed in these slides is courtesy of: Alberto Montresor, Werner Nutt, Kevin Wayne, Jon Kleinberg, Eva Tardos. A. Artale Algorithms for Data Processing Definition. P = set of decision problems for which there exists a poly-time algorithm. Problems and Algorithms – Decision Problems The Complexity Theory considers so called Decision Problems. • s Decision• Problem. X Input encoded asX a finite“yes” binary string ; • Decision ProblemA : Is conceived asX a set of strings on whichs the answer to the decision problem is ; yes if s ∈ X Algorithm for a decision problemA s receives an input string , and no if s 6∈ X ( ) = A. Artale Algorithms for Data Processing Problems and Algorithms – Decision Problems The Complexity Theory considers so called Decision Problems. • s Decision• Problem. X Input encoded asX a finite“yes” binary string ; • Decision ProblemA : Is conceived asX a set of strings on whichs the answer to the decision problem is ; yes if s ∈ X Algorithm for a decision problemA s receives an input string , and no if s 6∈ X ( ) = Definition. P = set of decision problems for which there exists a poly-time algorithm. A. Artale Algorithms for Data Processing Towards NP — Efficient Verification • • The issue here is the3-SAT contrast between finding a solution Vs. checking a proposed solution.I ConsiderI for example : We do not know a polynomial-time algorithm to find solutions; but Checking a proposed solution can be easily done in polynomial time (just plug 0/1 and check if it is a solution).
    [Show full text]
  • I Huvudet På Bender Futurama, Parodi, Satir Och Konsten Att Se På Tv
    Lunds universitet Oscar Jansson Avd. för litteraturvetenskap, SOL-centrum LIVR07 Handledare: Paul Tenngart 2012-05-30 I huvudet på Bender Futurama, parodi, satir och konsten att se på tv Innehållsförteckning Förord ......................................................................................................................................... 3 Inledning ..................................................................................................................................... 4 Tidigare forskning och utmärkelser ................................................................................... 7 Bender’s Head, urval och disposition ................................................................................ 9 Teoretiska ramverk och utgångspunkter .................................................................................. 11 Förförståelser, genre och tolkning .................................................................................... 12 Parodi, intertextualitet och implicita agenter ................................................................... 18 Parodi och satir i Futurama ...................................................................................................... 23 Ett inoriginellt medium? ................................................................................................... 26 Animerad sitcom vs. parodi ............................................................................................. 31 ”Try this, kids at home!”: parodins sammanblandade världar ........................................
    [Show full text]
  • BACCALAURÉAT-Session 2015
    BACCALAURÉAT-Session 2015 Epreuve de Discipline Non Linguistique Mathématiques/Anglais The Simpsons and their mathematical secrets Without doubt, the most mathematically sophisticated television show in the history of primetime broadcasting is The Simpsons. Al Jean, the executive producer, went to Harvard University to study mathematics at the age of just 16. Others have similarly impressive degrees in mathematics, and Jeff Westbrook resigned from a senior research post at Yale University to write scripts. "Colonel Homer" features the local movie theatre, called the Springfield Googolplex. In order to appreciate this reference, it is necessary to go back to 1938, when the mathematician Edward Kasner casually mentioned that it would be useful to have a label to describe the number 10100. His nine-year-old nephew Milton Sirotta suggested the word googol. At the same time, he gave a name for a still larger number: 'googolplex'. It was first suggested that a googolplex should be 1 followed by writing zeros until you get tired." The uncle rightly felt that the googolplex would then be a somewhat arbitrary and subjective number, so he redefined the googolplex as 10googol (that is 1 followed by a googol zeros) which is far more zeros that you could fit on a piece of paper the size of the observable universe, even if you used the smallest font imaginable. From The Guardian Weekly, 4thOctober, 2013 Questions 1. Make a short presentation of The Simpsons and the show's writing team. 2. a. How can you write differently the number 10100 ? The number 10−3? b. Explain the rules of powers, the main uses and advantages of powers of ten.
    [Show full text]
  • COMP 355 Advanced Algorithms NP-Completeness: General Definitions Chapter 8 Intro (KT)
    COMP 355 Advanced Algorithms NP-Completeness: General Definitions Chapter 8 Intro (KT) 1 Efficiency and Polynomial Time The notion of what we mean by efficient is quite vague. • If n is small, 2푛 run time may be just fine • When 푛 is huge, even 푛2 may be unacceptably slow 2 general classes of combinatorial problems • Those involving brute-force search of all feasible solutions, whose worst-case running time is an exponential function of the input size • Those that are based on a systematic solution, whose worst-case running time is a polynomial function of the input size. An algorithm is said to run in polynomial time if its worst-case running time is 푶(풏풄), where 푐 is a nonnegative constant. Higher worst-case running times, such as cn, 푛!, and 푛푛 are not polynomial time. 2 You can’t be serious! Arguments against using polynomial-time as the definition of efficiency • When n is small, run time of 2푛 much faster than 푂(푛20) • Many problems for which good average case solutions exist, but the worst case complexity may be very bad • On modern architectures, practical efficiency is a function of many issues that have to do with the machine’s internal architecture Mathematical advantages of defining “efficiently solvable” to be “worst- case polynomial time solvable” • The composition of two polynomials is a polynomial – Example: an algorithm that makes 푂(푛2) calls to a function that takes 푂(푛3) time runs in 푂(푛5) time, which is still polynomial. • No need to worry about the distribution of inputs When 푛 is sufficiently large, exponential time algorithms (2푛 time) are not efficient 3 The Emergence of Hard Problems “hard” problem = no known efficient algorithmic solutions exist for these problems.
    [Show full text]
  • The Simpsons and Futurama
    Chapter 24 Popular Culture in Teaching, Scholarship, and Outreach: The Simpsons and Futurama Sarah J. Greenwald Abstract Subject to thoughtful analysis of the benefits and challenges, popular culture can be an ideal source of fun ways to connect students and the general public to mathematics. My colleague Andrew Nestler and I created, class-tested, and widely shared activities related to the Twentieth Century Fox television show The Simpsons. The Scholarship of Teaching and Learning (SoTL) provides us with an analytic framework to develop, improve, and share our activities. We designed the activities to introduce or review important mathematical concepts and engage students. Later I expanded my interest into Futurama, another Twentieth Century Fox television show. I will describe informal outreach activities connected to both programs, including our educational website Simpsonsmath.com and my interactive lecture that audiences have accessed worldwide from a Futurama DVD. I will summarize the reception of my work by departmental colleagues, the institution, and the mathematical community. I will reflect on how this work has affected students and general audiences. I will also consider the direct and indirect impacts on my career and the unique challenges and rewards of working with popular culture in teaching, scholarship, and outreach. Key Words Popular culture, Outreach, SoTL, The Simpsons, Futurama MSC codes 00A09, 00A66, 97A40, 97A80, 97D40 24.1 Introduction Educators have a variety of methods available to them to deliver mathematical content and facilitate student engagement and learning. Mathematical cartoons can be a fun way to introduce or review concepts and reduce student anxiety (Schacht and Stewart 1990).
    [Show full text]
  • {TEXTBOOK} Love and Space Dust Ebook
    LOVE AND SPACE DUST Author: David Jones Number of Pages: 112 pages Published Date: 25 Apr 2014 Publisher: Createspace Independent Publishing Platform Publication Country: none Language: English ISBN: 9781499274813 DOWNLOAD: LOVE AND SPACE DUST Love And Space Dust PDF Book Learn to perform basic upgrades and prepare your PC for high-speed Internet connections, network connections, and added security, all with fully illustrated instructionsFind out how to expand memory, enhance speed, and update your computer's power supplyPrepare an old computer for Windows 7 and beef up your capacity for multimedia Upgrading Fixing Computers Do-It-Yourself For Dummies is a show-and-tell course in making your PC happy, healthy, and green. Genetic Databases: Socio-Ethical Issues in the Collection and Use of DNA"If you can't draw it, you don't know it:" that was the rule of the late neuroanatomist William DeMyer, MD. The book also discusses practical solutions for circumventing the correspondence problem, in particular the use of both distributional properties of lexical items and the phonological forms of such items in order to establish cognacy. This book goes behind the headlines to examine the conditions necessary not just for growth in Africa but for a wider business and economic transformation. Harris combines his in-depth knowledge of American history and culture with extensive archival research, and he has interviewed dozens of key players to reveal how Brown's showmanship transformed the National Gallery. Insurance. Khadiagala, David Keen, Chris Landsberg, Renu00e9 Lemarchand, Sarah Nouwen, 'Funmi Olonisakin and Eka Ikpe, Paul Omach, Aderoju Oyefusi, Sharath Srinivasan, and Dominik Zaum.
    [Show full text]
  • 8.3 Definition of NP Decision Problems
    8.3 Definition of NP Decision Problems Decision problem. X is a set of strings. Instance: string s. Algorithm A solves problem X: A(s) = yes iff s ∈ X. Polynomial time. Algorithm A runs in poly-time if for every string s, A(s) terminates in at most p(|s|) "steps", where p(⋅) is some polynomial. length of s PRIMES: X = { 2, 3, 5, 7, 11, 13, 17, 23, 29, 31, 37, …. } Algorithm. [Agrawal-Kayal-Saxena, 2002] p(|s|) = |s|8. 3 Definition of P P. Decision problems for which there is a poly-time algorithm. Problem Description Algorithm Yes No Grade school MULTIPLE Is x a multiple of y? 51, 17 51, 16 division RELPRIME Are x and y relatively prime? Euclid (300 BCE) 34, 39 34, 51 PRIMES Is x prime? AKS (2002) 53 51 EDIT Is the edit distance between Dynamic niether acgggt -DISTANCE x and y less than 5? programming neither ttttta Is there a vector x that Gauss-Edmonds 0 1 1 4 1 0 0 1 2 4 2 , 2 1 1 1 , 1 LSOLVE − satisfies Ax = b? elimination 0 3 15 36 0 1 1 1 € € 4 NP Certification algorithm intuition. Certifier views things from "managerial" viewpoint. Certifier doesn't determine whether s ∈ X on its own; rather, it checks a proposed proof t that s ∈ X. Def. Algorithm C(s, t) is a certifier for problem X if for every string s, s ∈ X iff there exists a string t such that C(s, t) = yes. "certificate" or "witness" NP. Decision problems for which there exists a poly-time certifier.
    [Show full text]
  • Girls Just Want to Have Sums to Air in the Spring Or Fall of 2006
    A W M Lie Sphere Transformations A Newton Polyhedron Method for Explicit Calculation of the Igusa Ellen K. Gasparovic, College of the Holy Cross Local Zeta Function Associated with a Degenerate Polynomial Advisor: Thomas Cecil, College of the Holy Cross Adrienne B. Rau, Barnard College, Columbia University Advisor: Margaret Robinson, Mount Holyoke College Nimber Sequences with no Preperiod for Three-Element Subtraction Sets In Search of an 8: Rank Computations Brittany C. Shelton, Montclair State University on a Family of Quartic Curves Advisor: Michael Jones, Montclair State University Kathleen Ansaldi, Loyola College of Maryland Advisor: Edray Goins, Purdue University Girls Just Want science. Now let’s see...Should I major in “femistry” or “galgebra”? [The Simpsons GABF12: Future-Drama] to Have Sums Jeff: It was for the Future-Drama episode where Lisa was Sarah J. Greenwald, Appalachian State University going to Yale and we were talking about what Yale was going to be like in the future, and the whole women in math The Simpsons is the longest-running sitcom of all time, thing was at the top of our brains at that point. and it is also one of the most literate television programs on the air, containing many references to subject matter and schol- Sarah: Around the Lawrence Summers time? ars from various academic fields, including mathematics. Jeff: Yes, exactly.... So we were thinking, “Well boys won’t be Andrew Nestler and I have found that the program is an in math anymore and they’ll be teaching ‘femistry’ and ideal source of fun ways to introduce important mathemati- ‘galgebra’ and all that kind of stuff....” cal concepts to students and to reduce math anxiety and motivate students in courses for non-majors.
    [Show full text]
  • Humor and Satire on Contemporary Television
    HUMOR AND SATIRE ON CONTEMPORARY TELEVISION This book examines contemporary American animated humor, focusing on popular animated television shows in order to explore the ways in which they engage with American culture and history, employing a peculiarly American way of using humor to discuss important cultural issues. With attention to the work of American humorists, such as the Southwest humorists, Mark Twain, Dorothy Parker, and Kurt Vonnegut, and the question of the extent to which modern animated satire shares the qualities of earlier humor, particularly the use of setting, the carnivalesque, collective memory, racial humor, and irony, Humor and Satire on Contemporary Television concentrates on a particular strand of American humor: the use of satire to expose the gap between the American ideal and the American experience. Taking up the notion of ‘The Great American Joke’, the author examines the discursive humor of programmes such as The Simpsons, South Park, Family Guy, King of the Hill, Daria, American Dad!, The Boondocks, The PJs and Futurama. A study of how animated television programmes offer a new discourse on a very traditional strain of American humor, this book will appeal to scholars and students of popular culture, television and media studies, American literature and visual studies, and contemporary humor and satire. Silas Kaine Ezell is Assistant Professor of English at Oklahoma Baptist University, USA. The Cultural Politics of Media and Popular Culture Series Editor: C. Richard King Washington State University, USA Dedicated to a renewed engagement with culture, this series fosters critical, contextual analyses and cross-disciplinary examinations of popular culture as a site of cultural poli- tics.
    [Show full text]
  • Slides by Kevin Wayne
    CS 580: Algorithm Design and Analysis Jeremiah Blocki Purdue University Spring 2018 Homework 4: Due tomorrow (March 9) at 11:59 PM Recap •Linear Programming • Very Powerful Technique (Subject of Entire Courses) • Our Focus: Using Linear Programming as a Tool • Solving Network Flow using Linear Programming • Finding Minimax Optimal Strategy in 2-Player Zero Sum Game • Operations Research (Brewery Example) •Solving Linear Programs • Simplex Intuition: • Optimal point is an “extreme point” • No “local optimum” • Simplex Runs in Exponential Time in Worst Case • But other algorithms (e.g., Ellipsoid) run in polynomial time 2 Chapter 8 NP and Computational Intractability Slides by Kevin Wayne. Copyright © 2005 Pearson-Addison Wesley. All rights reserved. 3 Algorithm Design Patterns and Anti-Patterns Algorithm design patterns. Ex. Greedy. O(n log n) interval scheduling. Divide-and-conquer. O(n log n) FFT. 2 Dynamic programming. O(n ) edit distance. 3 Duality. O(n ) bipartite matching. Reductions. Local search. Randomization. Algorithm design anti-patterns. k NP-completeness. O(n ) algorithm unlikely. k PSPACE-completeness. O(n ) certification algorithm unlikely. Undecidability. No algorithm possible. 4 8.1 Polynomial-Time Reductions Classify Problems According to Computational Requirements Q. Which problems will we be able to solve in practice? A working definition. [von Neumann 1953, Godel 1956, Cobham 1964, Edmonds 1965, Rabin 1966] Those with polynomial-time algorithms. Yes Probably no Shortest path Longest path Matching 3D-matching Min cut Max cut 2-SAT 3-SAT Planar 4-color Planar 3-color Bipartite vertex cover Vertex cover Primality testing Factoring 6 Classify Problems Desiderata. Classify problems according to those that can be solved in polynomial-time and those that cannot.
    [Show full text]
  • NP-Completeness ! J
    8.3 Definition of NP Chapter 8 NP and Computational Intractability Slides by Kevin Wayne. Copyright © 2005 Pearson-Addison Wesley. All rights reserved. 1 Decision Problems Definition of P Decision problem. P. Decision problems for which there is a poly-time algorithm. ! X is a set of strings. ! Instance: string s. ! Algorithm A solves problem X: A(s) = yes iff s ! X. Problem Description Algorithm Yes No Grade school MULTIPLE Is x a multiple of y? 51, 17 51, 16 Polynomial time. Algorithm A runs in poly-time if for every string s, division A(s) terminates in at most p(|s|) "steps", where p(") is some polynomial. RELPRIME Are x and y relatively prime? Euclid (300 BCE) 34, 39 34, 51 length of s PRIMES Is x prime? AKS (2002) 53 51 EDIT- Is the edit distance between Dynamic niether acgggt PRIMES: X = { 2, 3, 5, 7, 11, 13, 17, 23, 29, 31, 37, …. } DISTANCE x and y less than 5? programming neither ttttta Algorithm. [Agrawal-Kayal-Saxena, 2002] p(|s|) = |s|8. Is there a vector x that Gauss-Edmonds # 0 1 1& # 4& " 1 0 0% "1 % % 2 4 2( , % 2( $ 1 1 1' , $1 ' LSOLVE % " ( % ( $ ' $ ' satisfies Ax = b? elimination $% 0 3 15'( $% 36'( #$0 1 1&' #$1 &' ! ! 3 4 NP Certifiers and Certificates: Composite Certification algorithm intuition. COMPOSITES. Given an integer s, is s composite? ! Certifier views things from "managerial" viewpoint. ! Certifier doesn't determine whether s ! X on its own; Certificate. A nontrivial factor t of s. Note that such a certificate rather, it checks a proposed proof t that s ! X.
    [Show full text]
  • Year 11 Into 12 Transition Task One Subject Maths & Further Maths This
    Year 11 into 12 Transition Task One Subject Maths & Further Maths This work is intended to support your ability to successfully make the transition to A Level study. You do not need to send this work to us. 1. CGP Headstart to A-Level Maths You can buy this book for £10 or Amazon are currently doing the Kindle version for free. There is a diagnostic test for you to discover the weaknesses & revision pages for you to practice the skills. 2. Start looking at A-Level Calculators At Manor we recommend the Casio fx-991EX classwiz which you can get from Amazon for about £30 (but as of 3/5/2020 they have a deal for this calculator for £18.95). There are extra functions which will help at A-level on this new calculator. 3. Reading List: Alex’s Adventures in Numberland – Alex Bellos The world of maths can seem mind-boggling, irrelevant and, let's face it, boring. This groundbreaking book reclaims maths from the geeks. Mathematical ideas underpin just about everything in our lives: from the surprising geometry of the 50p piece to how probability can help you win in any casino. In search of weird and wonderful mathematical phenomena, Alex Bellos travels across the globe and meets the world's fastest mental calculators in Germany and a startlingly numerate chimpanzee in Japan. packed with fascinating, eye-opening anecdotes, Alex's Adventures in Numberland is an exhilarating cocktail of history, reportage and mathematical proofs that will leave you awestruck. The Simpsons and their Mathematical Secrets – Simon Singh Some have seen philosophy embedded in episodes of The Simpsons; Simon Singh reveals how the writers have drip-fed morsels of number theory into the series over the last twenty-five years; indeed, there are so many mathematical references in The Simpsons, and in its sister program, Futurama, that they could form the basis of an entire university course.
    [Show full text]