loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: João Paulo Coelho 1 ; Tatiana M. Pinho 2 and José Boaventura-Cunha 2

Affiliations: 1 Instituto Politécnico de Bragança and INESC TEC Technology and Science, Portugal ; 2 Universidade de Tr´as-os-Montes e Alto Douro, UTAD and INESC TEC Technology and Science, Portugal

ISBN: 978-989-758-157-1

Keyword(s): Population based Incremental Learning, Multi-Population Evolutionary Algorithms, FPGA.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: Evolutionary-based algorithms play an important role in finding solutions to many problems that are not solved by classical methods, and particularly so for those cases where solutions lie within extreme non-convex multidimensional spaces. The intrinsic parallel structure of evolutionary algorithms are amenable to the simultaneous testing of multiple solutions; this has proved essential to the circumvention of local optima, and such robustness comes with high computational overhead, though custom digital processor use may reduce this cost. This paper presents a new implementation of an old, and almost forgotten, evolutionary algorithm: the population-based incremental learning method. We show that the structure of this algorithm is well suited to implementation within programmable logic, as compared with contemporary genetic algorithms. Further, the inherent concurrency of our FPGA implementation facilitates the integration and testing of micro-populations.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.204.191.31

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:
Coelho, J.; Pinho, T. and Boaventura-Cunha, J. (2015). FPGA Implementation of a Multi-Population PBIL Algorithm.In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA, ISBN 978-989-758-157-1, pages 279-286. DOI: 10.5220/0005610402790286

@conference{ecta15,
author={João Paulo Coelho. and Tatiana M. Pinho. and José Boaventura{-}Cunha.},
title={FPGA Implementation of a Multi-Population PBIL Algorithm},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,},
year={2015},
pages={279-286},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005610402790286},
isbn={978-989-758-157-1},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,
TI - FPGA Implementation of a Multi-Population PBIL Algorithm
SN - 978-989-758-157-1
AU - Coelho, J.
AU - Pinho, T.
AU - Boaventura-Cunha, J.
PY - 2015
SP - 279
EP - 286
DO - 10.5220/0005610402790286

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.