Evolutionary Trained Radial Basis Function Networks for Robot Control

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F08%3A00321610" target="_blank" >RIV/67985807:_____/08:00321610 - isvavai.cz</a>

Result on the web

—

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Evolutionary Trained Radial Basis Function Networks for Robot Control

Original language description

In this paper, the radial basis function neural network is used as the control mechanism of the robot. Evolutionary algorithm is used to train the agent to perform several tasks. A comparison to multilayer perceptron neural networks and reinforcement learning is made and the results are discussed.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

—

Project

<a href="/en/project/KJB100300804" target="_blank" >KJB100300804: Neural Networks Learning Algorithms Based on Regularization Theory</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2008

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Control, Automation, Robotics and Vision

ISBN

978-1-4244-2286-9

ISSN

—

e-ISSN

—

Number of pages

6

Pages from-to

—

Publisher name

IEEE

Place of publication

Piscataway

Event location

Hanoi

Event date

Dec 17, 2008

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000266716600144