Title

Momentum Enhanced Neuroevolution

Keywords

DXNN; Evolutionary computation; Genetic algorithm; Memetic Algorithm; Momentum parameter; Neural network; Neuroevolution

Abstract

The momentum parameter is common within numerous optimization and local search algorithms, particularly in the popular back propagation neural network learning algorithm. Computationally cheap and prevalent in gradient descent approaches, it is not currently utilized within neuroevolution. In this paper we present some of the results produced by a momentum enhanced neuroevolutionary algorithm. We demonstrate how this computationally inexpensive parameter in most of the cases results in enhancing the system's performance.

Publication Date

7-11-2015

Publication Title

GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference

Number of Pages

1483-1484

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1145/2739482.2764709

Socpus ID

84959422228 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84959422228

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