A Quantum Field Evolution Strategy - An Adaptive Surrogate Approach

Jörg Bremer; Sebastian Lehnhoff

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

A Quantum Field Evolution Strategy - An Adaptive Surrogate Approach

Topics: Evolution Strategies; Swarm/Collective Intelligence

In Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 0IJCCI, 21-29, 2016 , Porto, Portugal

Authors: Jörg Bremer ¹ and Sebastian Lehnhoff ²

Affiliations: ¹ University of Oldenburg, Germany ; ² OFFIS, Germany

Keyword(s): Evolution Strategies, Global Optimization, Surrogate Optimization, Quantum Potential.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolution Strategies ; Evolutionary Computing ; Soft Computing ; Swarm/Collective Intelligence

Abstract: Evolution strategies have been successfully applied to optimization problems with rugged, multi-modal fitness landscapes, to non linear problems, and to derivative free optimization. Usually evolution is performed by exploiting the structure of the objective function. In this paper, we present an approach that harnesses the adapting quantum potential field determined by the spatial distribution of elitist solutions as guidance for the next generation. The potential field evolves to a smoother surface leveling local optima but keeping the global structure what in turn allows for a faster convergence of the solution set. We demonstrate the applicability and the competitiveness of our approach compared with particle swarm optimization and the well established evolution strategy CMA-ES.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 3.15.14.245

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

Paper citation in several formats:

Bremer, J. and Lehnhoff, S. (2016). A Quantum Field Evolution Strategy - An Adaptive Surrogate Approach. In Proceedings of the 8th International Joint Conference on Computational Intelligence (IJCCI 2016) - ECTA; ISBN 978-989-758-201-1, SciTePress, pages 21-29. DOI: 10.5220/0006037000210029

@conference{ecta16,
author={Jörg Bremer. and Sebastian Lehnhoff.},
title={A Quantum Field Evolution Strategy - An Adaptive Surrogate Approach},
booktitle={Proceedings of the 8th International Joint Conference on Computational Intelligence (IJCCI 2016) - ECTA},
year={2016},
pages={21-29},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006037000210029},
isbn={978-989-758-201-1},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Computational Intelligence (IJCCI 2016) - ECTA
TI - A Quantum Field Evolution Strategy - An Adaptive Surrogate Approach
SN - 978-989-758-201-1
AU - Bremer, J.
AU - Lehnhoff, S.
PY - 2016
SP - 21
EP - 29
DO - 10.5220/0006037000210029
PB - SciTePress