The Problem Space Theory
|
|
- Primrose Warner
- 5 years ago
- Views:
Transcription
1 The Problem Space Theory A problem space States o consists of states contain partial knowledge about the problem and about the solution Operators o transform states Search control knowledge o guides selection of operators o guides selection of states 11
2 Design Methods Observed. Design occurs mainly in algorithm design space. Schematic kernel idea quickly selected I. Successive refinement. Adapt very general operators o specific knowledge o means ends analysis. Symbolic and test-case execution of algorithms (in the absence of knowledge) Discovery and problem-solving in task space 13
3 Lessons about Design. A data flow space for representing partially specified algorithms. A variety of design schema (generate and test, divide and conquer) General operators instantiated with knowledge or by means-ends analysis Symbolic and test-case execution to expose problems and opportunities. A task space for test-case execution and discoveries. Discovery involves a prepared problem state Discovery requires recognition in the task space 27
4 Goals for Algorithm Design. Design algorithm sketches from semi-formal specifications Exploit knowledge if available Flexible in the absence of knowledge general problem solving and search
5 Alternative Automation Methods. Expert systems o successive refinement o mostly data and control structures o detailed and brittle o no problem solving or learning Formal derivation o small set of transformations o guarantee correctness o good local optimizations o lack focus, choice, transparency Inductive learning o input-output pairs or traces o schema matching and heuristic search o methods have not evolved much o possibilities if language is logic-based
6 Why Study Human Design? human thinking is flexible and robust programming details learned, not hand coded. people are resources to start and increment design knowledge. interfaces (automatic programmers must communicate with people)
7 Scientific Issues algorithm design (conquer new Al territory) formalize algorithm design principles, optimization, analysis program synthesis (do better than existing systems). discovery (conquer new Al phenomenon). - visual reasoning (critical-path Al phenomenon) shed light en kno Isdge/soarch Issues in expert systems * interaction off domain and programming knowledge in program synthesis how humans design and dfecover (confirm cognitive psychology theory)
8 The Protocol Analysis Approach Select a specific task (convexhull construction) Take protocols from appropriate subjects o subjects: faculty and graduate students in computer science o transcripts: complete text from audio tapes (videotaping would be better) Analyze protocols o need theory as basis o very detailed, phrase by phrase o refine theory as analysis proceeds
9 After the Analyses A simulation system (to test the theory) An automated design system An algorithm design assistant A protocol analysis aid Other programming tasks 6
10 A Task A point set and its convex hull
11 Sample of Protocol Episode 2 f L21 [»Minute 2«] Let's start with some point. L25 Either a point is on the hull or its not, right? L27 And the question is how to make this decision. Episode 3 Episode 3.1 L28 Let's take a few points here. (Draws 4 points.) L29 Well, that's not a good example, L30 because all four of them are on the convex hull. [S draws figure with 5 points not all in hull.] L35 OK, let's suppose I start with a point here. L36 And I'll just draw a line to some other point, right. L42 Now I can go in three directions from this point. L43 [»Minute 3«] I conjecture that L44 if it's the case that I can choose two points, L45 such that I can go on either side of the given line, L46 then this line can't be on the convex hull. L47 And I had better retreat. Episode 3.2 L63 Let's retreat, uh, back... back to A. L65 And choose some other point. L66 And this time we'll chose C. L67 Right? So now I have a line from A to C. 8
12 Protocol Sample continued Episode 3.4 L113 [»Minute 6«] And I see that, urn, L114 all the points are to one side of the line AC. L115 So I've got a candidate. L116 Now I'm at C and now I'll go again. L117 Choose some other point. L118 Suppose I choose B. [pause] LI19 A goes to C goes to B. L120 Urn, now I see that uh, [pause] L121 there are points on either side of the line CB, right, L122 there's E and there's A. L123 [»Minute 7«] I guess I have to look at A L124 even though I've already got a line segment from it. L125 So I know that the line CB can't be on the hull. L126 So I have to retreat back to C. L128 It looks like I'm not going to come up with a linear algorithm to do this.
13 Selected Episodes Episode El E2 E2.1 E3 E3.1 E3.1.1 E3.2 E3.3 E3.4 E3.4.1 E3.4.2 E3.4.3 E3.6 E3.6 E4 E6 Lines L1-L15 L16-L27 L22-L24 L28-L179 L28-L61 L28-L32 L62-L67 L68-L86 L86-L140 L86-L92 L93-L108 L127-L128 L141-L160 L161-L179 L180-L256 L256-L261 Description Acquire problem Design generate-and-test schema Interrupt(E2): specification of points Develop algorithm Find test Get example figure Decide how to handle test failure Find can discard interior start point Push algorithm all the way to find CH Return to previous state after E3.2 Interrupt(S): Exclude segment not point Interrupt(S): Greater than linear Develop initialization Recap algorithm Analyze complexity Termination (algorithm is first try)
14 A Problem-Space Model. What are the problem spaces? o an algorithm description space o a task domain space (geometry). What design methods are used? What are the operators and representations in the design space?. What is the task-domain knowledge?
15 Design Methods Observed. Design occurs mainly in algorithm design space Schematic kernel idea quickly selected. Successive refinement. Adapt very general operators o specific knowledge o means ends analysis. Symbolic and test-case execution of algorithms (in the absence of knowledge) Problem-solving in task space. Discovery 8
16 Basic Design Steps (occur as a result of productions firing) Select a problem (exposed during symbolic execution) Find kernel idea or solution plan Lay down basic structure (components) Elaborate details of structure Verify solution (optional, symbolic execution) Evaluate solution (e.g. time complexity) 14
17 Representation in DFS. Data-flow space (DFS) is main problem-solving space. represents partial algorithm designs (incomplete knowledge).o new information comes in small increments o postpone commitments. small vocabulary of basic components o arbitrary symbols and assertions (partially specified or alternative concepts) o expert vocabulary built up on top. components characterized by functional properties (not formal input-output relationships) o stable data dependencies in initial connections o internal representation by assertions o add assertions and additional inputs as needed o component can be refined to configuration 10
18 DFS Descriptions of Algorithm [pt],true >Generate >Test '. Assertions:, on {x}: on Test: elements are points predicate = is-on-hull(pt) " delete V [x] [yx] true {x} >Generate >Draw >{z hull-so-far} >Test t t false y delete Assertions: on {x}: on Generate: on {z}: on Test: elements are points ordering = random elements are segments predicate = not(points-both-sides(segment,{x})) 16
19 DFS Descriptions of Algorithm (new-component 'aeex>ry) (add-coaponent 'generator 'point-gen) (add-cooponent 'test 'side-test) (add-component 'memory nil 'add-elen) (arid-assertion 'point-gen '(Input-order-next)) (add-assert1on '(test-predicate (on-s1de test-in x-ax1s left)) 'side-test) (display-configuration 'subset) ************* * i MEHORY-1 > * a f f f > foimt-geii > f f *********#*** a has symbolic Hen S and has description Item S b has symbolic 1te«POINT-4 c has symbolic 1te«POINT-SET-3 _ -"> SIDE-TEST 4- f f Component GENERATOR-1 has assertions: INPUT-ORDER-NEXT Component TEST-1 has assertions: TEST-PREDICATE-1: (TEST-PREDICATE (ON-SIDE MAIN-INPUT X-AXIS LEFT)) ************ * *a MEMORY-2 f * c f 16
20 Applying Operators in DPS Edit DPS configuration - add,-modify or remove: o process components links input and output ports assertions items Map the operator onto the situation o simple instantiation by specific task-space or component rules o means ends analysis with subgoaling 18
21 I I Review of Design Principles. A data flow space for representing partially specified algorithms. A variety of design schema (generate and test, divide and conquer) General operators instantiated with knowledge or by means-ends analysis. Symbolic and test-case execution to expose problems and opportunities. A task space for test-case execution and discoveries. Discovery involves a prepared problem state Discovery requires recognition in the task space 23
22 I I Future Directions. discoveries example construction low level MEA adaptation. representations. algorithm analysis code generation/ program synthesis algorithm memory. analogy learning interactive assistant protocol analysis aid collect more protocols 24
Problem solving techniques for the design of algorithms
Carnegie Mellon University Research Showcase @ CMU Computer Science Department School of Computer Science 1982 Problem solving techniques for the design of algorithms Elaine Kant Carnegie Mellon University
More informationIs there a different way to get the same result? Did we give enough information? How can we describe the position? CPM Materials modified by Mr.
Common Core Standard: 8.G.3 Is there a different way to get the same result? Did we give enough information? How can we describe the position? CPM Materials modified by Mr. Deyo Title: IM8 Ch. 6.2.1 What
More informationBMO Round 1 Problem 6 Solutions
BMO 2005 2006 Round 1 Problem 6 Solutions Joseph Myers November 2005 Introduction Problem 6 is: 6. Let T be a set of 2005 coplanar points with no three collinear. Show that, for any of the 2005 points,
More informationFormal Methods of Software Design, Eric Hehner, segment 24 page 1 out of 5
Formal Methods of Software Design, Eric Hehner, segment 24 page 1 out of 5 [talking head] This lecture we study theory design and implementation. Programmers have two roles to play here. In one role, they
More informationLearning Task: Exploring Reflections and Rotations
Learning Task: Exploring Reflections and Rotations Name Date Mathematical Goals Develop and demonstrate an understanding of reflections and rotations of figures in general and on a coordinate plane. Essential
More informationPlanar convex hulls (I) Computational Geometry [csci 3250] Laura Toma Bowdoin College
Planar convex hulls (I) Computational Geometry [csci 3250] Laura Toma Bowdoin College Convex Hull Given a set P of points in 2D, their convex hull is the smallest convex polygon that contains all points
More informationAdvanced Algorithms Computational Geometry Prof. Karen Daniels. Fall, 2012
UMass Lowell Computer Science 91.504 Advanced Algorithms Computational Geometry Prof. Karen Daniels Fall, 2012 Voronoi Diagrams & Delaunay Triangulations O Rourke: Chapter 5 de Berg et al.: Chapters 7,
More informationCollege of Sciences. College of Sciences. Master s of Science in Computer Sciences Master s of Science in Biotechnology
Master s of Science in Computer Sciences Master s of Science in Biotechnology Department of Computer Sciences 1. Introduction\Program Mission The Program mission is to prepare students to be fully abreast
More informationRecursively Enumerable Languages, Turing Machines, and Decidability
Recursively Enumerable Languages, Turing Machines, and Decidability 1 Problem Reduction: Basic Concepts and Analogies The concept of problem reduction is simple at a high level. You simply take an algorithm
More informationHardware versus software
Logic 1 Hardware versus software 2 In hardware such as chip design or architecture, designs are usually proven to be correct using proof tools In software, a program is very rarely proved correct Why?
More informationEnhanced Entity-Relationship (EER) Modeling
CHAPTER 4 Enhanced Entity-Relationship (EER) Modeling Copyright 2017 Ramez Elmasri and Shamkant B. Navathe Slide 1-2 Chapter Outline EER stands for Enhanced ER or Extended ER EER Model Concepts Includes
More informationFeature-Oriented Domain Analysis (FODA) Feasibility Study
Feature-Oriented Domain Analysis (FODA) Feasibility Study Kyo C. Kang, Sholom G. Cohen, James A. Hess, William E. Novak, A. Spencer Peterson November 1990 Quick recap of DE terms Application: A system
More informationA Minimalist s Implementation of the 3-d Divide-and-Conquer Convex Hull Algorithm
A Minimalist s Implementation of the 3-d Divide-and-Conquer Convex Hull Algorithm Timothy M. Chan Presented by Dana K. Jansens Carleton University Simple Polygons Polygon = A consecutive set of vertices
More informationConic Sections and Locii
Lesson Summary: Students will investigate the ellipse and the hyperbola as a locus of points. Activity One addresses the ellipse and the hyperbola is covered in lesson two. Key Words: Locus, ellipse, hyperbola
More informationCS 410/584, Algorithm Design & Analysis, Lecture Notes 8!
CS 410/584, Algorithm Design & Analysis, Computational Geometry! Algorithms for manipulation of geometric objects We will concentrate on 2-D geometry Numerically robust try to avoid division Round-off
More informationDesign Sketching. Misused Metaphors. Interface Hall of Shame! Outline. Design Sketching
1 Design Sketching * slides marked Buxton are courtesy of, from his talk Why I Love the ipod, iphone, Wii and Google, remix uk, 18-19 Sept. 2008, Brighton Prof. James A. Landay University of Washington
More informationComputational geometry
Computational geometry Inge Li Gørtz CLRS Chapter 33.0, 33.1, 33.3. Computational Geometry Geometric problems (this course Euclidean plane). Does a set of line segments intersect, dividing plane into regions,
More informationMITOCW watch?v=sdw8_0rdzuw
MITOCW watch?v=sdw8_0rdzuw PROFESSOR: Directed acyclic graphs are a special class of graphs that really have and warrant a theory of their own. Of course, "directed acyclic graphs" is lot of syllables,
More informationCS 410/584, Algorithm Design & Analysis, Lecture Notes 8
CS 410/584,, Computational Geometry Algorithms for manipulation of geometric objects We will concentrate on 2-D geometry Numerically robust try to avoid division Round-off error Divide-by-0 checks Techniques
More informationLecture 25: Bezier Subdivision. And he took unto him all these, and divided them in the midst, and laid each piece one against another: Genesis 15:10
Lecture 25: Bezier Subdivision And he took unto him all these, and divided them in the midst, and laid each piece one against another: Genesis 15:10 1. Divide and Conquer If we are going to build useful
More informationWWW.STUDENTSFOCUS.COM REPRESENTATION OF KNOWLEDGE Game playing - Knowledge representation, Knowledge representation using Predicate logic, Introduction to predicate calculus, Resolution, Use of predicate
More informationComputational Geometry
Lecture 1: Introduction and convex hulls Geometry: points, lines,... Geometric objects Geometric relations Combinatorial complexity Computational geometry Plane (two-dimensional), R 2 Space (three-dimensional),
More informationUnit 1, Lesson 1: Moving in the Plane
Unit 1, Lesson 1: Moving in the Plane Let s describe ways figures can move in the plane. 1.1: Which One Doesn t Belong: Diagrams Which one doesn t belong? 1.2: Triangle Square Dance m.openup.org/1/8-1-1-2
More informationCSC-461 Exam #2 April 16, 2014
Pledge: On my honor, I pledge that I have not discussed any of the questions on this exam with fellow students, nor will I until after 7 p.m. tonight. Signed: CSC-461 Exam #2 April 16, 2014 Name Time Started:
More informationVocabulary for Student Discourse Pre-image Image Reflect Symmetry Transformation Rigid transformation Congruent Mapping Line of symmetry
Lesson 3 - page 1 Title: Reflections and Symmetry I. Before Engagement Duration: 2 days Knowledge & Skills Understand transformations as operations that map a figure onto an image Understand characteristics
More informationA Roadmap to an Enhanced Graph Based Data mining Approach for Multi-Relational Data mining
A Roadmap to an Enhanced Graph Based Data mining Approach for Multi-Relational Data mining D.Kavinya 1 Student, Department of CSE, K.S.Rangasamy College of Technology, Tiruchengode, Tamil Nadu, India 1
More informationMITOCW ocw f99-lec07_300k
MITOCW ocw-18.06-f99-lec07_300k OK, here's linear algebra lecture seven. I've been talking about vector spaces and specially the null space of a matrix and the column space of a matrix. What's in those
More informationMITOCW watch?v=4dj1oguwtem
MITOCW watch?v=4dj1oguwtem PROFESSOR: So it's time to examine uncountable sets. And that's what we're going to do in this segment. So Cantor's question was, are all sets the same size? And he gives a definitive
More informationRange Minimum Queries Part Two
Range Minimum Queries Part Two Recap from Last Time The RMQ Problem The Range Minimum Query (RMQ) problem is the following: Given a fixed array A and two indices i j, what is the smallest element out of
More informationLattice Polygon s and Pick s Theorem From Dana Paquin and Tom Davis 1 Warm-Up to Ponder
Lattice Polygon s and Pick s Theorem From Dana Paquin and Tom Davis http://www.geometer.org/mathcircles/pick.pdf 1 Warm-Up to Ponder 1. Is it possible to draw an equilateral triangle on graph paper so
More information3. Voronoi Diagrams. 3.1 Definitions & Basic Properties. Examples :
3. Voronoi Diagrams Examples : 1. Fire Observation Towers Imagine a vast forest containing a number of fire observation towers. Each ranger is responsible for extinguishing any fire closer to her tower
More informationChapter 8: Enhanced ER Model
Chapter 8: Enhanced ER Model Subclasses, Superclasses, and Inheritance Specialization and Generalization Constraints and Characteristics of Specialization and Generalization Hierarchies Modeling of UNION
More informationLast time. Reasoning about programs. Coming up. Project Final Presentations. This Thursday, Nov 30: 4 th in-class exercise
Last time Reasoning about programs Coming up This Thursday, Nov 30: 4 th in-class exercise sign up for group on moodle bring laptop to class Final projects: final project presentations: Tue Dec 12, in
More informationReasoning about programs
Reasoning about programs Last time Coming up This Thursday, Nov 30: 4 th in-class exercise sign up for group on moodle bring laptop to class Final projects: final project presentations: Tue Dec 12, in
More informationMIAMI-DADE COUNTY PUBLIC SCHOOLS District Pacing Guide GEOMETRY HONORS Course Code:
Topic V: Quadrilaterals Properties Pacing Date(s) Traditional 22 days 10/24/13-11/27/13 Block 11 days 10/24/13-11/27/13 COMMON CORE STATE STANDARD(S) & MATHEMATICAL PRACTICE (MP) NEXT GENERATION SUNSHINE
More informationENERGY SCHEMING 1.0. G.Z. Brown, Tomoko Sekiguchi. Department of Architecture, University of Oregon Eugene, Oregon USA
ENERGY SCHEMING 1.0 G.Z. Brown, Tomoko Sekiguchi Department of Architecture, University of Oregon Eugene, Oregon 97403 USA ABSTRACT This paper describes software for the Apple Macintosh microcomputer that
More informationClass Discussion. Line m is called a line of reflection and point O is called the midpoint. b. What relationship occurs between line m and segment
Name: Geometry Pd. 1-3 Notes Date: Learning Goal: What is a reflection? How do you perform various reflections? Class Discussion As we prepare to work with reflections, we need to examine some relationships
More informationDatabase Management System Prof. Partha Pratim Das Department of Computer Science & Engineering Indian Institute of Technology, Kharagpur
Database Management System Prof. Partha Pratim Das Department of Computer Science & Engineering Indian Institute of Technology, Kharagpur Lecture - 19 Relational Database Design (Contd.) Welcome to module
More information3D convex hulls. Computational Geometry [csci 3250] Laura Toma Bowdoin College
3D convex hulls Computational Geometry [csci 3250] Laura Toma Bowdoin College Convex Hull in 3D The problem: Given a set P of points in 3D, compute their convex hull convex polyhedron 2D 3D polygon
More informationArchitectural Prescriptions for Dependable Systems
Architectural Prescriptions for Dependable Systems Manuel Brandozzi, Dewayne E. Perry UT ARISE, Advanced Research In Software Engineering. The University of Texas at Austin, Austin TX 78712-1084 {MBrandozzi,
More informationFormStream a Workflow Prototyping Tool for Classroom Use
FormStream a Workflow Prototyping Tool for Classroom Use Paul Juell and Benjamin Dischinger Department of Computer Science North Dakota State University Computer Science NDSU Fargo, ND 58105 paul.juell@ndsu.edu
More information2-1 Transformations and Rigid Motions. ENGAGE 1 ~ Introducing Transformations REFLECT
2-1 Transformations and Rigid Motions Essential question: How do you identify transformations that are rigid motions? ENGAGE 1 ~ Introducing Transformations A transformation is a function that changes
More informationGeometry Assessments. Chapter 2: Patterns, Conjecture, and Proof
Geometry Assessments Chapter 2: Patterns, Conjecture, and Proof 60 Chapter 2: Patterns, Conjecture, and Proof Introduction The assessments in Chapter 2 emphasize geometric thinking and spatial reasoning.
More information1 Linear Programming. 1.1 Optimizion problems and convex polytopes 1 LINEAR PROGRAMMING
1 LINEAR PROGRAMMING 1 Linear Programming Now, we will talk a little bit about Linear Programming. We say that a problem is an instance of linear programming when it can be effectively expressed in the
More informationThe University of Jordan. Accreditation & Quality Assurance Center. Curriculum for Doctorate Degree
Accreditation & Quality Assurance Center Curriculum for Doctorate Degree 1. Faculty King Abdullah II School for Information Technology 2. Department Computer Science الدكتوراة في علم الحاسوب (Arabic).3
More informationRegular Expressions. An Alternate Approach by Bob Mathews
Regular Expressions n lternate pproach by ob Mathews In this month's challenge, we were asked to check a number of constraints with regular expressions For example, the string does not contain Of course,
More information3D convex hulls. Computational Geometry [csci 3250] Laura Toma Bowdoin College
3D convex hulls Computational Geometry [csci 3250] Laura Toma Bowdoin College Convex Hulls The problem: Given a set P of points, compute their convex hull 2D 3D 2D 3D polygon polyhedron Polyhedron region
More informationReasoning About Programs Panagiotis Manolios
Reasoning About Programs Panagiotis Manolios Northeastern University March 1, 2017 Version: 101 Copyright c 2017 by Panagiotis Manolios All rights reserved. We hereby grant permission for this publication
More informationI can identify reflections, rotations, and translations. I can graph transformations in the coordinate plane.
Page! 1 of! 14 Attendance Problems. 1. Sketch a right angle and its angle bisector. 2. Draw three different squares with (3, 2) as one vertex. 3. Find the values of x and y if (3, 2) = (x + 1, y 3) Vocabulary
More informationLines That Intersect Circles
LESSON 11-1 Lines That Intersect Circles Lesson Objectives (p. 746): Vocabulary 1. Interior of a circle (p. 746): 2. Exterior of a circle (p. 746): 3. Chord (p. 746): 4. Secant (p. 746): 5. Tangent of
More informationUnit 6: Rigid Motion Congruency
Name: Geometry Period Unit 6: Rigid Motion Congruency In this unit you must bring the following materials with you to class every day: Please note: Pencil This Booklet A device This booklet will be scored
More informationAdapted from: The Human Factor: Designing Computer Systems for People, Rubinstein & Hersh (1984) Designers make myths. Users make conceptual models.
User Interface Guidelines UI Guidelines 1 Adapted from: The Human Factor: Designing Computer Systems for People, Rubinstein & Hersh (1984) Know your users - they are not you Designers make myths. Users
More informationMITOCW watch?v=kz7jjltq9r4
MITOCW watch?v=kz7jjltq9r4 PROFESSOR: We're going to look at the most fundamental of all mathematical data types, namely sets, and let's begin with the definitions. So informally, a set is a collection
More informationMath 3 - Lesson Title: Using the Coordinate Plane for Proofs
Targeted Content Standard(s): Use coordinates to prove simple geometric theorems algebraically. G.GPE.4 Use coordinates to prove simple geometric theorems algebraically. For example, prove or disprove
More informationCS103 Spring 2018 Mathematical Vocabulary
CS103 Spring 2018 Mathematical Vocabulary You keep using that word. I do not think it means what you think it means. - Inigo Montoya, from The Princess Bride Consider the humble while loop in most programming
More informationMathematical Logic Part One
Mathematical Logic Part One Question: How do we formalize the logic we've been using in our proofs? Where We're Going Propositional Logic (Today) Basic logical connectives. Truth tables. Logical equivalences.
More informationCCM6+/7+ - Unit 13 - Page 1 UNIT 13. Transformations CCM6+/7+ Name: Math Teacher: Projected Test Date:
CCM6+/7+ - Unit 13 - Page 1 UNIT 13 Transformations CCM6+/7+ Name: Math Teacher: Projected Test Date: Main Idea Pages Unit 9 Vocabulary 2 Translations 3 10 Rotations 11 17 Reflections 18 22 Transformations
More informationStudents are not expected to work formally with properties of dilations until high school.
Domain: Geometry (G) Cluster: Understand congruence and similarity using physical models, transparencies, or geometry software. Standard: 8.G.1. Verify experimentally the properties of rotations, reflections,
More informationMaximizing the Area of a Garden
Math Objectives Students will determine the relationship between the width and length of a garden with a rectangular shape and a fixed amount of fencing. The garden is attached to a barn, and exactly three
More informationFinding sets of points without empty convex 6-gons. Mark H. Overmars
Finding sets of points without empty convex 6-gons Mark H. Overmars UU-CS-2001-07 February 2001 Finding sets of points without empty convex 6-gons Mark Overmars Department of Information and Computing
More informationIntroduction to Software Engineering
Chapter 1 Introduction to Software Engineering Content 1. Introduction 2. Components 3. Layered Technologies 4. Generic View of Software Engineering 4. Generic View of Software Engineering 5. Study of
More informationConvex Hull Algorithms
Convex Hull Algorithms Design and Analysis of Algorithms prof. F. Malucelli Villa Andrea e Ceriani Simone Outline Problem Definition Basic Concepts Bruteforce Algorithm Graham Scan Algorithm Divide and
More informationPROFESSOR: Last time, we took a look at an explicit control evaluator for Lisp, and that bridged the gap between
MITOCW Lecture 10A [MUSIC PLAYING] PROFESSOR: Last time, we took a look at an explicit control evaluator for Lisp, and that bridged the gap between all these high-level languages like Lisp and the query
More informationDirect Variations DIRECT AND INVERSE VARIATIONS 19. Name
DIRECT AND INVERSE VARIATIONS 19 Direct Variations Name Of the many relationships that two variables can have, one category is called a direct variation. Use the description and example of direct variation
More informationTranscript: A Day in the Life of a K12 Seventh Grade Teacher
Transcript: A Day in the Life of a K12 Seventh Grade Teacher Transcript (Video) Transcript (Video with Audio Description) Transcript (Audio Description) Transcript (Video) 00:00:00.000 MUSIC 00:00:05.799
More informationHigh-Level Information Interface
High-Level Information Interface Deliverable Report: SRC task 1875.001 - Jan 31, 2011 Task Title: Exploiting Synergy of Synthesis and Verification Task Leaders: Robert K. Brayton and Alan Mishchenko Univ.
More informationSpring 2016 Algorithms Midterm Exam (Show your work to get full credit!)
Spring 2016 Algorithms Midterm Exam (Show your work to get full credit!) March 18, 2016 "Plagiarism is the intentional or unintentional use of the words or ideas of another without acknowledging their
More informationManual Control Unit GFCD 16
Manual Control Unit 1400002_EN/04.2017 Index 1. Main features 3 2. Technical features 3 3. Installation guidelines 4 4. Preliminary checks 5 5. Electrical connections 5 6. Filter taps 5 7. Settings 6 8.
More informationCS 373: Combinatorial Algorithms, Fall Name: Net ID: Alias: U 3 / 4 1
CS 373: Combinatorial Algorithms, Fall 2000 Homework 1 (due November 16, 2000 at midnight) Starting with Homework 1, homeworks may be done in teams of up to three people. Each team turns in just one solution,
More informationComputational Geometry: Lecture 5
Computational Geometry: Lecture 5 Don Sheehy January 29, 2010 1 Degeneracy In many of the algorithms that we have discussed so far, we have run into problems when that input is somehow troublesome. For
More informationThe for Loop. Lesson 11
The for Loop Lesson 11 Have you ever played Tetris? You know that the game never truly ends. Blocks continue to fall one at a time, increasing in speed as you go up in levels, until the game breaks from
More informationAlgebra. Chapter 4: FUNCTIONS. Name: Teacher: Pd:
Algebra Chapter 4: FUNCTIONS Name: Teacher: Pd: Table of Contents Day1: Chapter 4-1: Relations SWBAT: (1) Identify the domain and range of relations and functions (2) Match simple graphs with situations
More informationFocus of this Unit: Connections to Subsequent Learning: Approximate Time Frame: 4-6 weeks Connections to Previous Learning:
Approximate Time Frame: 4-6 weeks Connections to Previous Learning: In Grade 8, students are introduced to the concepts of congruence and similarity through the use of physical models and dynamic geometry
More informationFormal Model. Figure 1: The target concept T is a subset of the concept S = [0, 1]. The search agent needs to search S for a point in T.
Although this paper analyzes shaping with respect to its benefits on search problems, the reader should recognize that shaping is often intimately related to reinforcement learning. The objective in reinforcement
More informationUnit 3.2: Fractions, Decimals and Percent Lesson: Comparing and Ordering Fractions and Decimals
Unit 3.2: Fractions, Decimals and Percent Lesson: Comparing and Ordering Fractions and Decimals Objectives: Students will use benchmarks, place value and equivalent fractions to compare and order fractions
More informationSECTION SIX Teaching/ Learning Geometry. General Overview
SECTION SIX Teaching/ Learning Geometry General Overview The learning outcomes for Geometry focus on the development of an understanding of the properties of three-dimensional and plane shapes and how
More informationUnit 14: Transformations (Geometry) Date Topic Page
Unit 14: Transformations (Geometry) Date Topic Page image pre-image transformation translation image pre-image reflection clockwise counterclockwise origin rotate 180 degrees rotate 270 degrees rotate
More informationLesson 3 Transcript: Part 1 of 2 - Tools & Scripting
Lesson 3 Transcript: Part 1 of 2 - Tools & Scripting Slide 1: Cover Welcome to lesson 3 of the db2 on Campus lecture series. Today we're going to talk about tools and scripting, and this is part 1 of 2
More informationMIAMI-DADE COUNTY PUBLIC SCHOOLS District Pacing Guide GEOMETRY HONORS Course Code:
Topic II: Transformations in the Plane Pacing Date(s) Traditional 14 09/15/14-10/03/14 Block 07 09/15/14-10/03/14 MATHEMATICS FLORIDA STANDARDS & MATHEMATICAL PRACTICE (MP) MATHEMATICAL PRACTICE (MP) ESSENTIAL
More informationUser Guide. 980 DisplayPort Link Layer Sink Compliance Tests
User Guide 980 DisplayPort Link Layer Sink Compliance Tests Rev: A1 Page 1 March 24, 2017 Table of Contents 1 Overview 3 1.1 Scope of this User Guide 3 1.2 Changes to this User Guide 4 1.3 What options
More informationFinding Measures of Angles Formed by Transversals Intersecting Parallel Lines
Lesson 22 Finding Measures of Angles Formed by Transversals Intersecting Parallel Lines 8.G.5 1 Getting the idea The figure below shows two parallel lines, j and k. The parallel lines,, are intersected
More informationTopic: Geometry Gallery Course: Mathematics 1
Student Learning Map Unit 3 Topic: Geometry Gallery Course: Mathematics 1 Key Learning(s): Unit Essential Question(s): 1. The interior and exterior angles of a polygon can be determined by the number of
More informationBasic Triangle Congruence Lesson Plan
Basic Triangle Congruence Lesson Plan Developed by CSSMA Staff Drafted August 2015 Prescribed Learning Outcomes: Introduce students to the concept of triangle congruence and teach them about the congruency
More information1/60. Geometric Algorithms. Lecture 1: Introduction. Convex Hulls
1/60 Geometric Algorithms Lecture 1: Introduction Convex Hulls Geometric algorithms scope 2/60 Geometry algorithms (practice): Study of geometric problems that arise in various applications and how algorithms
More informationVoronoi Diagrams. A Voronoi diagram records everything one would ever want to know about proximity to a set of points
Voronoi Diagrams Voronoi Diagrams A Voronoi diagram records everything one would ever want to know about proximity to a set of points Who is closest to whom? Who is furthest? We will start with a series
More informationReflection and Refraction
Reflection and Refraction Theory: Whenever a wave traveling in some medium encounters an interface or boundary with another medium either (or both) of the processes of (1) reflection and (2) refraction
More informationOn Constraint Problems with Incomplete or Erroneous Data
On Constraint Problems with Incomplete or Erroneous Data Neil Yorke-Smith and Carmen Gervet IC Parc, Imperial College, London, SW7 2AZ, U.K. nys,cg6 @icparc.ic.ac.uk Abstract. Real-world constraint problems
More information3D Modeling of Roofs from LiDAR Data using the ESRI ArcObjects Framework
3D Modeling of Roofs from LiDAR Data using the ESRI ArcObjects Framework Nadeem Kolia Thomas Jefferson High School for Science and Technology August 25, 2005 Mentor: Luke A. Catania, ERDC-TEC Abstract
More informationWe have already studied equations of the line. There are several forms:
Chapter 13-Coordinate Geometry extended. 13.1 Graphing equations We have already studied equations of the line. There are several forms: slope-intercept y = mx + b point-slope y - y1=m(x - x1) standard
More informationnotes13.1inclass May 01, 2015
Chapter 13-Coordinate Geometry extended. 13.1 Graphing equations We have already studied equations of the line. There are several forms: slope-intercept y = mx + b point-slope y - y1=m(x - x1) standard
More informationThe SUMO Speaker Series for Undergraduates. The Art Gallery Problem
The SUMO Speaker Series for Undergraduates (food from Pizza Chicago) Wednesday, April 21 4:40-5:30, room 380C The Art Gallery Problem Amy Pang Abstract: Imagine you are the curator of an art gallery with
More informationCSS 503 Program 1: Parallelizing a Convex-Hull Program with Multi-Processes Professor: Munehiro Fukuda Due date: see the syllabus
CSS 503 Program 1: Parallelizing a Convex-Hull Program with Multi-Processes Professor: Munehiro Fukuda Due date: see the syllabus 1. Purpose In this programming assignment, we will parallelize a convex
More informationGraphical Models. David M. Blei Columbia University. September 17, 2014
Graphical Models David M. Blei Columbia University September 17, 2014 These lecture notes follow the ideas in Chapter 2 of An Introduction to Probabilistic Graphical Models by Michael Jordan. In addition,
More informationCPS 310 first midterm exam, 2/26/2014
CPS 310 first midterm exam, 2/26/2014 Your name please: Part 1. More fun with forks (a) What is the output generated by this program? In fact the output is not uniquely defined, i.e., it is not necessarily
More informationLesson 16: More on Modeling Relationships with a Line
Student Outcomes Students use the least squares line to predict values for a given data set. Students use residuals to evaluate the accuracy of predictions based on the least squares line. Lesson Notes
More informationSTUDENT LESSON A9 Recursion
STUDENT LESSON A9 Recursion Java Curriculum for AP Computer Science, Student Lesson A9 1 STUDENT LESSON A9 Recursion INTRODUCTION: Recursion is the process of a method calling itself as part of the solution
More informationDrawing hypergraphs using NURBS curves
Drawing hypergraphs using NURBS curves Ronny Bergmann Institute of Mathematics University of Lu beck presentation at the Kolloquium der Institute fu r Mathematik und Informatik November 25th, 2009 Content
More information15-451/651: Algorithms CMU, Spring 2016 Lecture #24: Computational Geometry Introduciton April 13, 2015 Lecturer: Danny Sleator
15-451/651: Algorithms CMU, Spring 2016 Lecture #24: Computational Geometry Introduciton April 13, 2015 Lecturer: Danny Sleator 1 Introduction Computational geometry is the design and analysis of algorithms
More informationIn our first lecture on sets and set theory, we introduced a bunch of new symbols and terminology.
Guide to and Hi everybody! In our first lecture on sets and set theory, we introduced a bunch of new symbols and terminology. This guide focuses on two of those symbols: and. These symbols represent concepts
More informationWhat's the Slope of a Line?
What's the Slope of a Line? These lines look pretty different, don't they? Lines are used to keep track of lots of info -- like how much money a company makes. Just off the top of your head, which of the
More information