Genetic Programming: 19th European Conference

Book Description

This book constitutes the refereed proceedings of the 19th European Conference on Genetic Programming, EuroGP 2016, held in Porto, Portugal, in March/April 2016 co-located with the Evo*2016 events: EvoCOP, EvoMUSART, and EvoApplications.

The 11 revised full papers presented together with 8 poster papers were carefully reviewed and selected from 36 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics as diverse as semantic methods, recursive programs, grammatical methods, coevolution, Cartesian GP, feature selection, metaheuristics, evolvability, and fitness predictors; and applications including image processing, one-class classification, injection attacks, numerical modelling, streaming data classification, creation and optimisation of circuits, multi-class classification, scheduling in manufacturing and wireless networks.

Table of Contents

Full Presentations
One-Class Classification for Anomaly Detection with Kernel Density Estimation and Genetic Programming
Evolutionary Approximation of Edge Detection Circuits
On the Impact of Class Imbalance in GP Streaming Classification with Label Budgets
Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data
Surrogate Fitness via Factorization of Interaction Matrix
Scheduling in Heterogeneous Networks Using Grammar-Based Genetic Programming
On the Analysis of Simple Genetic Programming for Evolving Boolean Functions
Genetic Programming Based Hyper-heuristics for Dynamic Job Shop Scheduling: Cooperative Coevolutionary Approaches
A Genetic Programming Approach for the Traffic Control Problem with Epigenetic Modifications
A Genetic Programming-Based Imputation Method for Classification with Missing Data
Plastic Fitness Predictors Coevolved with Cartesian Programs

Short Presentations
Search-Based SQL Injection Attacks Testing Using Genetic Programming
Grammar for Derivation Tree Based Genetic Programming Systems
Modelling Evolvability in Genetic Programming
Towards Automated Strategies in Satisfiability Modulo
Geometric Semantic Genetic Programming Is Overkill
Semantic Geometric Initialization
Patterns for Constructing Mutation Operators: Limiting the Search Space in a Application
Iterative Cartesian Genetic Programming: Creating General Algorithms for Solving Travelling Salesman Problems

Book Details

Download LinkFormatSize (MB)Upload Date
Download from UpLoadedTrue PDF1301/05/2017
Download from ZippyShareTrue PDF1306/28/2016
How to Download? Report Dead Links & Get a Copy