Constraint programming | Search algorithms

Difference-map algorithm

The difference-map algorithm is a search algorithm for general constraint satisfaction problems. It is a meta-algorithm in the sense that it is built from more basic algorithms that perform projections onto constraint sets. From a mathematical perspective, the difference-map algorithm is a dynamical system based on a mapping of Euclidean space. Solutions are encoded as fixed points of the mapping. Although originally conceived as a general method for solving the phase problem, the difference-map algorithm has been used for the boolean satisfiability problem, protein structure prediction, Ramsey numbers, diophantine equations, and Sudoku, as well as sphere- and disk-packing problems. Since these applications include NP-complete problems, the scope of the difference map is that of an . Whereas incomplete algorithms can efficiently verify solutions (once a candidate is found), they cannot prove that a solution does not exist. The difference-map algorithm is a generalization of two iterative methods: Fienup's Hybrid input output (HIO) algorithm for phase retrieval and the for convex optimization. Iterative methods, in general, have a long history in phase retrieval and convex optimization. The use of this style of algorithm for hard, non-convex problems is a more recent development. (Wikipedia).

Difference-map algorithm
Video thumbnail

Intersection and union of sets 2

drawing intersection and union with geogebra. this video can help you to drawing sets.

From playlist Go Geogebra

Video thumbnail

Intersection of Planes on Geogebra

In this video, we look at a strategy for finding the intersection of planes on Geogebra.

From playlist Geogebra

Video thumbnail

Planar Graphs - Intro to Algorithms

This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.

From playlist Introduction to Algorithms

Video thumbnail

Find the Shortest Path - Intro to Algorithms

This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.

From playlist Introduction to Algorithms

Video thumbnail

06 More about mappings

In this tutorial I show a few more notations and share a few more thoughts on mappings.

From playlist Abstract algebra

Video thumbnail

What are parallel lines and a transversal

👉 Learn about converse theorems of parallel lines and a transversal. Two lines are said to be parallel when they have the same slope and are drawn straight to each other such that they cannot meet. In geometry, parallel lines are identified by two arrow heads or two small lines indicated i

From playlist Parallel Lines and a Transversal

Video thumbnail

What’s the difference of two squares?

This is a short animation showing one way to think of the difference of squares formula (at least when the two numbers involved are positive). #manim #math #proofwithoutwords #visualproof

From playlist Algebra

Video thumbnail

What is the Symmetric Difference of 2 Sets?

What is the symmetric difference of 2 sets? In this video we go over the symmetric difference of sets, explaining it in a couple ways including what is probably the briefest way. The symmetric difference of two sets A and B is (A union B)-(A intersect B). If you need to know what the defin

From playlist Set Theory

Video thumbnail

Project 1: Logistic Map (Part A) | Lecture 11 | Numerical Methods for Engineers

Getting ready to do a numerical calculation of the logistic map. Let's first learn a little theory. Join me on Coursera: https://www.coursera.org/learn/numerical-methods-engineers Lecture notes at http://www.math.ust.hk/~machas/numerical-methods-for-engineers.pdf Subscribe to my chan

From playlist Numerical Methods for Engineers

Video thumbnail

Conformal Geometry Processing

Symposium on Geometry Processing 2017 Graduate School Lecture by Keenan Crane https://www.cs.cmu.edu/~kmcrane/ http://geometry.cs.ucl.ac.uk/SGP2017/?p=gradschool#abs_conformal_geometry Digital geometry processing is the natural extension of traditional signal processing to three-dimensi

From playlist Tutorials and Lectures

Video thumbnail

Introduction to Motion Planning Algorithms | Motion Planning with the RRT Algorithm, Part 1

Motion planning lets robots or vehicles plan an obstacle-free path from a start to goal state. Learn some popular motion planning algorithms, how they work, and their applicability in different scenarios. Watch the full video series: https://youtube.com/playlist?list=PLn8PRpmsu08qQorl_KLr

From playlist Motion Planning Using RRT Algorithm

Video thumbnail

Mobile Robotics, Part 5: Performing a Sequence of Path Navigation Tasks

Learn how to design a supervisory logic that navigates a robot through a predefined path. Enter the MATLAB and Simulink Primary and Secondary School Competitions Hub: https://bit.ly/2JBr3jf Download Example Files: https://bit.ly/2XNktPt ---------------------------------------------------

From playlist MATLAB and Simulink Mobile Robotics

Video thumbnail

Sarah Percival 7/27/22: Computation of Reeb Graphs in a Semi-Algebraic Setting

The Reeb graph is a tool from Morse theory that has recently found use in applied topology due to its ability to track changes in connectivity of level sets of a function. In this talk, I will motivate the use of semi-algebraic geometry as a setting for problems in applied topology and sho

From playlist AATRN 2022

Video thumbnail

Jeff Erickson - Lecture 2 - Two-dimensional computational topology - 19/06/18

School on Low-Dimensional Geometry and Topology: Discrete and Algorithmic Aspects (http://geomschool2018.univ-mlv.fr/) Jeff Erickson (University of Illinois at Urbana-Champaign, USA) Two-dimensional computational topology - Lecture 2 Abstract: This series of lectures will describe recent

From playlist Jeff Erickson - School on Low-Dimensional Geometry and Topology: Discrete and Algorithmic Aspects

Video thumbnail

Marina Meilă: "Manifold Learning"

Machine Learning for Physics and the Physics of Learning Tutorials 2019 "Manifold Learning" Marina Meilă, University of Washington Institute for Pure and Applied Mathematics, UCLA September 6, 2019 For more information: http://www.ipam.ucla.edu/programs/workshops/machine-learning-for-ph

From playlist Machine Learning for Physics and the Physics of Learning 2019

Video thumbnail

MuZero

The video explains MuZero! MuZero makes AlphaZero more general by constructing representation and dynamics models such that it can play games without a perfect model of the environment. This dynamics function is unique because of the way it's hidden state is tied into the policy and value

From playlist Game Playing AI: From AlphaGo to MuZero

Video thumbnail

How to Change Algorithms (PyVis and Python Tutorial 06)

In this video, we explore the different algorithms available in PyVis: Barnes-Hut, ForcedAtlas, and H-Repulsion. On the Barnes-Hut Algorithm, see: (http://arborjs.org/docs/barnes-hut) For the json file, either visit my post on pythonhumanities.com: https://pythonhumanities.com/python-and-

From playlist How to Use PyVis Library in Python Tutorials

Video thumbnail

Skew Lines, Perpendicular & Parallel Lines & Planes, Intersecting Lines & Transversals

This geometry video tutorial provides a basic introduction into skew lines. It explains the difference between parallel lines, perpendicular lines, skew lines, intersecting lines, and transversals. Parallel lines are coplanar lines that do not intersect. Skew lines are noncoplanar lines

From playlist Geometry Video Playlist

Video thumbnail

Ximena Fernández 7/20/22: Morse theory for group presentations and the persistent fundamental group

Discrete Morse theory is a combinatorial tool to simplify the structure of a given (regular) CW-complex up to homotopy equivalence, in terms of the critical cells of discrete Morse functions. In this talk, I will present a refinement of this theory that guarantees not only a homotopy equiv

From playlist AATRN 2022

Related pages

Constraint satisfaction | Support (mathematics) | Absolute value | Dynamical system | Fixed point (mathematics) | Sudoku | Discrete Fourier transform | Map (mathematics) | Phase problem | Literal (mathematical logic) | Convex optimization | Unitary transformation | Search algorithm | Boolean satisfiability problem | Chaos theory | Euclidean space | Projection (linear algebra) | Local search (optimization) | Constraint (mathematics)