'Fitness sharing' presentation slideshows

Hybrid Systems

Hybrid Systems. Hybridization. Integrated architectures for machine learning have been shown to provide performance improvements over single representation architectures.

652 views • 57 slides

Co-Evolution and Speciation

335 views • 32 slides

Multimodal Problems and Spatial Distribution

Multimodal Problems and Spatial Distribution. Chapter 9. Motivation 1: Multimodality. Most interesting problems have more than one locally optimal solution. Motivation 2: Genetic Drift. Finite population with global (panmictic) mixing and selection eventually convergence around one optimum

260 views • 25 slides

Multimodal Problems and Spatial Distribution

Multimodal Problems and Spatial Distribution. From: A.E. Eiben and J.E. Smith, Introduction to Evolutionary Computing Multimodal Problems and Spatial Distribution. Motivation 1: Multimodality. Most interesting problems have more than one locally optimal solution. Motivation 2: Genetic Drift.

260 views • 25 slides

A Hybrid Sequential Niche Genetic Algorithm for Multimodal Objective Functions

Midwest Regional Conference, 2007. A Hybrid Sequential Niche Genetic Algorithm for Multimodal Objective Functions. Jeonghwa Moon, Libin Zhang and Andreas A. Linninger Date :08/24/07 University of Illinois at Chicago, Chicago, IL Laboratory for Product and Process Design,

544 views • 23 slides

CAP6938 Neuroevolution and Developmental Encoding NeuroEvolution of Augmenting Topologies (NEAT)

CAP6938 Neuroevolution and Developmental Encoding NeuroEvolution of Augmenting Topologies (NEAT). Dr. Kenneth Stanley September 25, 2006. TWEANN Problems Reminder. Competing conventions problem Topology matching problem Initial population topology randomization Defective starter genomes

411 views • 22 slides

CAP6938 Neuroevolution and Developmental Encoding NeuroEvolution of Augmenting Topologies (NEAT)

CAP6938 Neuroevolution and Developmental Encoding NeuroEvolution of Augmenting Topologies (NEAT). Dr. Kenneth Stanley September 25, 2006. TWEANN Problems Reminder. Competing conventions problem Topology matching problem Initial population topology randomization Defective starter genomes

231 views • 22 slides

Speciation/Niching

Speciation/Niching. The original SGA (Simple GA) is designed to rapidly search the landscape (exploration) and zoom in (exploitation) on a single solution .

193 views • 18 slides

The Problem

Resource-Based Fitness Sharing Jeffrey Horn Northern Michigan University Department of Mathematics and Computer Science Marquette, MI USA jhorn@nmu.edu http://cs.nmu.edu/~jeffhorn PPSN VII September 10, 2002. The Problem.

227 views • 17 slides

Artificial Speciation and Automatic Modularisation

Artificial Speciation and Automatic Modularisation. Neural Network Ensemble. A group of neural networks is used to solve a problem; each perhaps concentrating on part of the dataset The final output of the ensemble is determined by combining the output of individual NN using: Majority Voting

204 views • 8 slides