Deriving Ramsey Numbers Interim Project Evaluations Team 7 Albuquerque Academy.

Slides:



Advertisements
Similar presentations
Testing Relational Database
Advertisements

Algorithm Design Techniques
C++ Programming:. Program Design Including
Chapter 7 User-Defined Methods. Chapter Objectives  Understand how methods are used in Java programming  Learn about standard (predefined) methods and.
Algorithm Strategies Nelson Padua-Perez Chau-Wen Tseng Department of Computer Science University of Maryland, College Park.
ClearEye: An Visualization System for Document Revision CPSC 533C Project Update Qiang Kong Qixing Zheng.
Algorithms and Problem Solving-1 Algorithms and Problem Solving.
ECIV 301 Programming & Graphics Numerical Methods for Engineers Lecture 4 Programming and Software EXCEL and MathCAD.
Algorithms and Problem Solving. Learn about problem solving skills Explore the algorithmic approach for problem solving Learn about algorithm development.
Overview of The Operations Research Modeling Approach.
Prof. Bodik CS 164 Lecture 171 Register Allocation Lecture 19.
Register Allocation (via graph coloring)
Chapter 11 Limitations of Algorithm Power Copyright © 2007 Pearson Addison-Wesley. All rights reserved.
Algorithms. Introduction Before writing a program: –Have a thorough understanding of the problem –Carefully plan an approach for solving it While writing.
Recursion Chapter 7. Chapter 7: Recursion2 Chapter Objectives To understand how to think recursively To learn how to trace a recursive method To learn.
Advanced Topics in Algorithms and Data Structures 1 Two parallel list ranking algorithms An O (log n ) time and O ( n log n ) work list ranking algorithm.
Introduction to Simulated Annealing 22c:145 Simulated Annealing  Motivated by the physical annealing process  Material is heated and slowly cooled.
Data Structures Introduction Phil Tayco Slide version 1.0 Jan 26, 2015.
Chapter 9 High-Level Programming Languages: C++. Chapter Goals Describe the expectations of high level languages Distinguish between functional design.
Problem Solving Methods. Class Objectives Learn to apply the problem solving process Learn techniques for error-free problem solving.
สาขาวิชาเทคโนโลยี สารสนเทศ คณะเทคโนโลยีสารสนเทศ และการสื่อสาร.
Lecture 8. How to Form Recursive relations 1. Recap Asymptotic analysis helps to highlight the order of growth of functions to compare algorithms Common.
Data Structures & AlgorithmsIT 0501 Algorithm Analysis I.
1 Chapter 24 Developing Efficient Algorithms. 2 Executing Time Suppose two algorithms perform the same task such as search (linear search vs. binary search)
Invitation to Computer Science, Java Version, Second Edition.
Recursion Chapter 7. Chapter Objectives  To understand how to think recursively  To learn how to trace a recursive method  To learn how to write recursive.
Numerical Methods Applications of Loops: The power of MATLAB Mathematics + Coding 1.
An Introduction to Programming and Algorithms. Course Objectives A basic understanding of engineering problem solving process. A basic understanding of.
Warm-up 1.Find f(12). 2.f(x)=140. Find x.. Answer 1.f(12) = 1 2. f(9) = 140.
Computer Science Department Data Structure & Algorithms Lecture 8 Recursion.
Design of a real time strategy game with a genetic AI By Bharat Ponnaluri.
More Algorithm Design CSIS 1595: Fundamentals of Programming and Problem Solving 1.
Loop Application: Numerical Methods, Part 1 The power of Matlab Mathematics + Coding.
Theory of Algorithms: Brute Force. Outline Examples Brute-Force String Matching Closest-Pair Convex-Hull Exhaustive Search brute-force strengths and weaknesses.
Major objective of this course is: Design and analysis of modern algorithms Different variants Accuracy Efficiency Comparing efficiencies Motivation thinking.
1 Lower Bounds Lower bound: an estimate on a minimum amount of work needed to solve a given problem Examples: b number of comparisons needed to find the.
1 CPSC 320: Intermediate Algorithm Design and Analysis July 28, 2014.
CS221 Algorithm Basics. What is an algorithm? An algorithm is a list of instructions that transform input information into a desired output. Each instruction.
Group 8: Denial Hess, Yun Zhang Project presentation.
Inequalities and their Graphs Objective: To write and graph simple inequalities with one variable.
Chapter 9 Efficiency of Algorithms. 9.3 Efficiency of Algorithms.
Solving Network Coding Problems with Genetic Algorithmic Methods Anthony Kim Advisers: Muriel Medard and Una-May O’Reilly.
LESSON 7.4 Function Notation To learn function notation To evaluate functions by substitution, by using the graphs drawn by hand, and on the graphing calculator.
(C)opyright 2000 Scott/Jones Publishers Introduction to Flowcharting.
Optimization Problems
Ricochet Robots Mitch Powell Daniel Tilgner. Abstract Ricochet robots is a board game created in Germany in A player is given 30 seconds to find.
Think Possibility 1 Iterative Constructs ITERATION / LOOPS C provides three loop structures: the for-loop, the while-loop, and the do-while-loop. Each.
Chapter 15: Recursion. Objectives In this chapter, you will: – Learn about recursive definitions – Explore the base case and the general case of a recursive.
Hash Tables and Hash Maps. DCS – SWC 2 Hash Tables A Set and a Map are both abstract data types – we need a concrete implemen- tation in order to use.
MD5 & Hash Encryption By Alex Buzak. Overview Purpose of MD5 and Hash Encryptions Examples MD5 Algorithm Explanation of Possible Security Risks Practical.
1 The Software Development Process ► Systems analysis ► Systems design ► Implementation ► Testing ► Documentation ► Evaluation ► Maintenance.
Onlinedeeneislam.blogspot.com1 Design and Analysis of Algorithms Slide # 1 Download From
Design of a real time strategy game with a genetic AI By Bharat Ponnaluri.
TCSS 342 Autumn 2004 Version TCSS 342 Data Structures & Algorithms Autumn 2004 Ed Hong.
Graphs. Graph Definitions A graph G is denoted by G = (V, E) where  V is the set of vertices or nodes of the graph  E is the set of edges or arcs connecting.
Chapter 15: Recursion. Objectives In this chapter, you will: – Learn about recursive definitions – Explore the base case and the general case of a recursive.
1 BUILDING JAVA PROGRAMS CHAPTER 5 PROGRAM LOGIC AND INDEFINITE LOOPS.
#1 Make sense of problems and persevere in solving them How would you describe the problem in your own words? How would you describe what you are trying.
(Proof By) Induction Recursion
Advanced Algorithms Analysis and Design
INTRODUCTION TO PROBLEM SOLVING
Problem Solving: Brute Force Approaches
Welcome to Math 3 honors.
Objective of This Course
Differential Equations
Theory of Computation Turing Machines.
Chapter 11 Limitations of Algorithm Power
Data Structures Introduction
Recursive Thinking.
Learning Combinational Logic
Presentation transcript:

Deriving Ramsey Numbers Interim Project Evaluations Team 7 Albuquerque Academy

February 24, 2007Deriving Ramsey Numbers: Team 7, Albuquerque Academy2 Contents Definitions Problem Statement Method and Mathematical Model Explored Algorithm Possibilities Expected Results Current Overall Progress Plans for the Future Questions

February 24, 2007Deriving Ramsey Numbers: Team 7, Albuquerque Academy3 Definitions Ramsey numbers part of mathematical field of graph theory k m is defined as a graph containing m nodes and all possible line between the nodes Ramsey functions notated as K(r, b)=n –K is Ramsey function –r, b are independent variables –n is result of Ramsey function; called Ramsey number Ramsey function gives smallest graph size that when colored in any pattern of only two colors, will not contain sub-graphs of size r or b (i.e. does not contain a k r or k b )

February 24, 2007Deriving Ramsey Numbers: Team 7, Albuquerque Academy4 Definitions Possible to create a mapping without a k 3 in a 5-node graph (a k 5 ) Example: R(3,3) = 6 Not possible to create a coloring without a k 3 in a 6- node graph (a k 6 ) and this R(3,3) = 6

February 24, 2007Deriving Ramsey Numbers: Team 7, Albuquerque Academy5 Problem Statement Create program to find Ramsey number K(r,b) for given r and b

February 24, 2007Deriving Ramsey Numbers: Team 7, Albuquerque Academy6 Method and Mathematical Model Begin at starting graph See if this graph fits the parameters of the inputs (m and n) Systematically recolor the graph and repeat Continue doing this until all graphs are tested If no graphs succeed, the answer is found Otherwise try a graph with one more node

February 24, 2007Deriving Ramsey Numbers: Team 7, Albuquerque Academy7 Explored Algorithm Possibilities Eliminate some unnecessary graphs Work from graphs that are known to work with one less node Only try a few to see if those graphs can be eliminated by: Symmetry Correcting problem areas

February 24, 2007Deriving Ramsey Numbers: Team 7, Albuquerque Academy8 Expected Results Successfully calculate Ramsey numbers for small values of inputs r, b Make improvements over “brute force” base- speed in computing time required to calculate Ramsey numbers Still require significant amounts of computing time and power to calculate Ramsey numbers for larger inputs of r, b, as modern programs have encountered

February 24, 2007Deriving Ramsey Numbers: Team 7, Albuquerque Academy9 Current Overall Progress Have completed thorough research phase –Found information on Ramsey number research and discovered solutions –Found mathematical theorems to assist in developing algorithm and reducing neccesary computing time and power –Found basic information on past attempts at creating a program to calculate Ramsey numbers

February 24, 2007Deriving Ramsey Numbers: Team 7, Albuquerque Academy10 Current Overall Progress Have basics of code for first version of program –Create map using Hash Map dynamic data structure in Java: HashMap Frank = new HashMap(n); //Frank (Ramsey's first name) is THE map –Query the user for the inputs: String temp; temp = JOptionPane.showInputDialog(null, "How many points would you like in the map?",“Deriving Ramsey Numbers :: Input", JOptionPane.QUESTION_MESSAGE ); –Will likely use objects to represent the line segments to create consistency when re-coloring.

February 24, 2007Deriving Ramsey Numbers: Team 7, Albuquerque Academy11 Plans for the Future Continue writing program –Initially, work with a “brute force” algorithm –Later, implement our more advanced and time saving algorithm Continue to develop the algorithm based on experience while writing program Prepare final report summarizing our research

Questions