Visual Sequences IQ Tests 1 Dipendra Kumar Misra (Y9201) Mukul Singh (Y9350) Tags : Search, Pattern Recognition, Logic etc Advisor : Dr. Amitabh Mukherjee.

Slides:



Advertisements
Similar presentations
Techniques for Combinational Logic Optimization
Advertisements

From Verification to Synthesis Sumit Gulwani Microsoft Research, Redmond August 2013 Marktoberdorf Summer School Lectures: Part 1.
Synthesizing Geometry Constructions Sumit Gulwani MSR, Redmond Vijay Korthikanti UIUC Ashish Tiwari SRI.
Automated Grading of DFA Constructions Rajeev Alur (Penn), Loris D’Antoni (Penn), Sumit Gulwani (MSR), Bjoern Hartmann (Berkeley), Dileep Kini (UIUC),
Model Checking I What are LTL and CTL?. and or dreq q0 dack q0bar.
Geometric Sequences.
6-1 Chapter Goals Determine whether a problem is suitable for a computer solution Describe the computer problem-solving process and relate it to Polya’s.
Chapter 6 Problem Solving and Algorithm Design. 6-2 Chapter Goals Determine whether a problem is suitable for a computer solution Describe the computer.
CS 355 – Programming Languages
Counting Techniques: Combinations
1 Module 13 Studying the internal structure of REC, the set of solvable problems –Complexity theory overview –Automata theory preview Motivating Problem.
ISBN Chapter 1 Preliminaries. Copyright © 2004 Pearson Addison-Wesley. All rights reserved.1-2 Chapter 1 Topics Motivation Programming Domains.
Fitting a Model to Data Reading: 15.1,
Tefko Saracevic, Rutgers University 1 Practice for logical operators Boolean search statements and Venn diagrams.
ISBN Chapter 1 Topics Motivation Programming Domains Language Evaluation Criteria Influences on Language Design Language Categories Language.
Chapter 2: Algorithm Discovery and Design
Chapter 2: Algorithm Discovery and Design
1 Lecture 11 Studying structure of REC –Complexity theory overview –Automata theory preview Motivating Problem –string searching.
1 Lecture 14 Studying the internal structure of REC, the set of solvable problems –Complexity theory overview –Automata theory preview Motivating Problem.
1 Chapter 2 Problem Solving Techniques INTRODUCTION 2.2 PROBLEM SOLVING 2.3 USING COMPUTERS IN PROBLEM SOLVING : THE SOFTWARE DEVELOPMENT METHOD.
Unit 10 – Logic and Venn Diagrams
Building Adders & Sub tractors Dr Ahmed Telba. Introducing adder circuits Adder circuits are essential inside microprocessors as part of the ALU, or arithmetic.
SVD(Singular Value Decomposition) and Its Applications
1 L07SoftwareDevelopmentMethod.pptCMSC 104, Version 8/06 Software Development Method Topics l Software Development Life Cycle Reading l Section 1.4 – 1.5.
Modeling and representation 1 – comparative review and polygon mesh models 2.1 Introduction 2.2 Polygonal representation of three-dimensional objects 2.3.
Mathematical Problem Solving Math 6320 Summer 2006.
Ch1 AI: History and Applications Dr. Bernard Chen Ph.D. University of Central Arkansas Spring 2011.
Artificial Intelligence Introduction (2). What is Artificial Intelligence ?  making computers that think?  the automation of activities we associate.
Lecture 1 Note: Some slides and/or pictures are adapted from Lecture slides / Books of Dr Zafar Alvi. Text Book - Aritificial Intelligence Illuminated.
Supporting Automatic Model Inconsistency Fixing Yingfei Xiong University of Tokyo, Japan Zhenjiang HuNational Institute of Informatics, Japan Haiyan ZhaoPeking.
Dr Scott Turner. Why do you needed to develop problem solving skills?  One definition of programming is it is applied problem solving  You have a problem.
Chapter 2: Algorithm Discovery and Design Invitation to Computer Science, C++ Version, Third Edition.
Programming by Examples Marktoberdorf Lectures August 2015 Sumit Gulwani.
Artificial Intelligence Introductory Lecture Jennifer J. Burg Department of Mathematics and Computer Science.
Dimensions in Synthesis Part 3: Ambiguity (Synthesis from Examples & Keywords) Sumit Gulwani Microsoft Research, Redmond May 2012.
Overview of Formal Methods. Topics Introduction and terminology FM and Software Engineering Applications of FM Propositional and Predicate Logic Program.
The Development Process Problem Solving. Problem Solving - Dr. Struble 2 What Is Asked of Computer Programmers? Input Transformation Output Write a computer.
CHAPTER ONE Problem Solving and the Object- Oriented Paradigm.
ALGORITHM CHAPTER 8. Chapter Outlines and Objectives  Define an algorithm and relate it to problem solving.  Define three construct and describe their.
Week 10Complexity of Algorithms1 Hard Computational Problems Some computational problems are hard Despite a numerous attempts we do not know any efficient.
Artificial Intelligence: Introduction Department of Computer Science & Engineering Indian Institute of Technology Kharagpur.
Simultaneously Learning and Filtering Juan F. Mancilla-Caceres CS498EA - Fall 2011 Some slides from Connecting Learning and Logic, Eyal Amir 2006.
Compositional Program Synthesis from Natural Language and Examples Mohammad Raza, Sumit Gulwani & Natasa Milic-Frayling Microsoft.
A Classification-based Approach to Question Answering in Discussion Boards Liangjie Hong, Brian D. Davison Lehigh University (SIGIR ’ 09) Speaker: Cho,
Conceptual Design Dr. Dania Bilal IS588 Spring 2008.
Music in Artificial Intelligence Victoria Tran. Why Music in Artificial Intelligence? Technology is improving every day, so music is beginning to depend.
Unit B Constructing Complex Searches Internet Research Third Edition.
INVITATION TO Computer Science 1 11 Chapter 2 The Algorithmic Foundations of Computer Science.
3.4 Notes: Factoring p. 74 in your book. FACTORING We’ll use the Sum and Product Technique We’ll use the Sum and Product Technique Our job is to find.
CS 404Ahmed Ezzat 1 CS 404 Introduction to Compiler Design Lecture 1 Ahmed Ezzat.
Example 4 Using Multiplication Properties SOLUTION Identity property of multiplication () 16 a. 6 = Find the product. () 16 a.b. 15– () 0 Multiplication.
 In a small group create a definition of rigor as it applies in education.
Sumit Gulwani Programming by Examples Applications, Algorithms & Ambiguity Resolution Keynote at IJCAR June 2016.
CENG 424-Logic for CS Introduction Based on the Lecture Notes of Konstantin Korovin, Valentin Goranko, Russel and Norvig, and Michael Genesereth.
- photometric aspects of image formation gray level images
Social networking tools (powerpoint extract)
Concepts of Engineering and Technology Introduction to Problem Solving
Discrete Structure II: Introduction
Finding rational numbers between rational numbers
CSE3302 Programming Languages (things to say)
CSc4730/6730 Scientific Visualization
Multiple Aspect Modeling of the Synchronous Language Signal
Chapter 5: Control Structure
Evaluate the limit: {image} Choose the correct answer from the following:
Do Now: Solve and Graph.
Introduction to Artificial Intelligence Instructor: Dr. Eduardo Urbina
Learn how to choose the best strategy to solve the problem.
Artificial Intelligence
Presentation transcript:

Visual Sequences IQ Tests 1 Dipendra Kumar Misra (Y9201) Mukul Singh (Y9350) Tags : Search, Pattern Recognition, Logic etc Advisor : Dr. Amitabh Mukherjee Dr. Sumit Gulwani

Sample Problem 2 Which Image logically follows the Input Sequence

Motivation Automate Manual Verification of Intelligence Problems Synthesis of IQ Problems Insights into cognitive studies Visual Problems combine both Logic and Geometry 3

Background Work IQ problems have been studied for a long time Fanya Montalvo [1986, 1993] discusses topics such as Diagram Understanding “It will be hard for a computer program to solve picture problems” – Sanghi & Dowe 4

Case Study No Formal Definition of IQ problems Separate Semantic Based problems from Syntax Based problems Case Study on over 100 problems from standard books and online tests 5

Our Intuition “A Transformation Language with few transformations like Rotation and Shading should be powerful enough to cover a large subset of problems” 6

Methodology Front End Back End Set of Images ( Test Set and Solution Set ) Solution 7

Front End L1 Set of Images (Test Set and solution set) Set of Lines, Circles and Special Objects detected in the image set L2 Polygons formed by combining suitable lines 8

Back End Transformation of P1 = T1 ∩ T3 U T2 ∩ (T4 U T5) 9 P1 P2 P3 P4 P6 P5 T2 T1 T3 T4 T5

Ranking Method Rank(P,Q) = MatchPrimitive(P,Q) + MatchPrimitive(Q,P) MatchPrimitive(P,Q) = Number of Primitive of P in Q 10

Lets Do Some Practice 11

Handling Ambiguity Multiple Transformations – Use Least Complex Formula (Kolmogorov) 12 P AB Q AB R 270R 90 R 270 Choosing Cross Terms (90,270) will give us wrong answer

Results Solve Visual Problems for a Large Subset Zero Human Intervention No restriction on type of primitives – apple, cap, chair etc. 13

References & Resources “IQ Tests to Keep You Sharp” by Philip Carter and Kenneth Russel “Check Your IQ” by Ken Russell and Philip Carter Spreadsheet Data Manipulation Using Examples S. Gulwani POPL 2011 A computer program capable of passing IQ tests, Sanghi, P. and Dowe 2003 Montalvo, Fanya S. Diagram understanding,