'Genetic programming' presentation slideshows

Automatic program repair using genetic programming

1.71k views • 161 slides

Engineering Optimization and Nature

Engineering Optimization and Nature. Ender Ayanoglu Center for Pervasive Communications and Computing The Henry Samueli School of Engineering University of California, Irvine Calit2 UC Irvine Division Workshop on Biological and Computing/Communication Systems July 6, 2009.

641 views • 50 slides

The League Championship Algorithm: A new algorithm for numerical function optimization

The League Championship Algorithm: A new algorithm for numerical function optimization. By: A. H. Kashan. Introduction. Since the 1970s that the idea of a general algorithmic framework, which can be applied with relatively few modifications to different optimization problems , emerged.

974 views • 45 slides

Genetic Algorithms

Genetic Algorithms. Introduction. After scientists became disillusioned with classical and neo-classical attempts at modeling intelligence, they looked in other directions. Two prominent fields arose, connectionism (neural networking, parallel processing) and evolutionary computing.

881 views • 43 slides

TEXTURE AND SHADING

TEXTURE AND SHADING. Presented by Vishal Dalmiya University of Texas at Arlington Electrical Engineering Department. MILESTONES. TEXTURE TEXTURE CLASSIFICATION STATISTICAL METHODS FOR TEXTURE ANALYSIS GRAY-LEVEL CO-OCCURRENCE MATRIX ENTROPY HOMOGENEITY AUTOCORRELATION

707 views • 38 slides

Introduction to Genetic Algorithms

528 views • 34 slides

Evolutionary Computation

Evolutionary Computation. Khaled Rasheed Computer Science Dept. University of Georgia http://www.cs.uga.edu/~khaled. Presentation outline. Genetic algorithms Genetic programming Classifier systems Evolution programming Conclusion. In the forest. Fitness = Height

492 views • 31 slides

Evolving a Solution: Developmental Plasticity in Evolutionary Computation

366 views • 27 slides

Heuristic learning

Heuristic learning. Intelligent Information Analysis based on V-Graph knowledge representation. Speech Plot. Problem Redundancy / Insufficiency / Corruption of input data. Representation Learning Recode Intrinsic Confliction Heuristic Learning

355 views • 24 slides

Dan Bower

305 views • 19 slides

MKI44: Evolutionary Algorithms

MKI44: Evolutionary Algorithms. Organisation. Teachers. Ida Sprinkhuizen-Kuyper Room B.02.39 E-mail: i.kuyper@donders.ru.nl Phone: 024-3616126 URL: http://www.nici.ru.nl/~idak

307 views • 19 slides

Introduction to Evolutionary Algorithms Session 4

Introduction to Evolutionary Algorithms Session 4. Jim Smith University of the West of England, UK May/June 2012. Overview. Example of learning models from data Continuous Representations Tree-based Representations Practical session with Genetic Programming. Real valued problems.

270 views • 18 slides

CSC4504/Prolog. : Formal Languages & Applications J Paul Gibson, A207 paul.gibson@int-edu.eu

CSC4504/Prolog. : Formal Languages & Applications J Paul Gibson, A207 paul.gibson@int-edu.eu http://www-public. it-sudparis.eu /~ gibson/Teaching/CSC4504/. Genetic Algorithms /~ gibson / Teaching /CSC4504/L5-GeneticAlgorithms.pdf.

407 views • 17 slides

Medical Data Mining Using Fuzzy Evolutionary Computing

Medical Data Mining Using Fuzzy Evolutionary Computing. Abdul Razak Hussain 1 October 2002. Contents. Introduction Literature Review Methodology Summary. Introduction. Overview Background of problem Statement of problem Purpose of study. Overview. Medical/Biological databases

362 views • 16 slides

The Traveling Salesman Problem

1.24k views • 16 slides

Genetic Programming and Artificial Neural Networks

Genetic Programming and Artificial Neural Networks. COSC 4V82 Michael Samborski 16 November 2012. Overview. Artificial Neural Network Review The First to Try It Developmental Approaches Good Ideas Always Come Back Comparison to Other Evolutionary ANN techniques.

432 views • 14 slides

Reinforcement learning

Svetlana Lockwood Washington State University CptS 540 Fall 2010. Reinforcement learning . Background. Dates back to the early days of cybernetics. Goal : to program agents by reward and punishment without needing to specify how the task is to be achieved. BUT

279 views • 14 slides

Population-based metaheuristics

262 views • 11 slides

Composition Steps

Composition Steps. 01/10/2013. Agenda. Retooling note Define composition Wrapper without function pointer Compositions (thus far ) Evolutionary computation discussion. Retooling. Issue found with codebase Compiled with .cc extension defaulted to g++

216 views • 10 slides

Hydroinformatics : Data Mining in Hydrology

Hydroinformatics : Data Mining in Hydrology . IIHR Seminar (December 3, 2010 ) Evan Roz. UNESCO-IHE, Delft, Dr. Solomatine. Hydroinformatics t echniques were adopted from computational intelligence (CI)/intelligent systems/machine learning hydroinformatics

588 views • 10 slides