Performance Comparison of Relational Reinforcement Learning and RBF Neural Networks for Small Mobile Robots
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F08%3A00331007" target="_blank" >RIV/67985807:_____/08:00331007 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Performance Comparison of Relational Reinforcement Learning and RBF Neural Networks for Small Mobile Robots
Original language description
A performance of two learning mechanisms for small mobile robots is performed in this paper. Relational reinforcement learning, and radial basis function neural network learned by evolutionary algorithm are trained to perform the same maze exploration task and the results were compared in terms learning speed, accuracy and compactness of the resulting control mechanisms. Advantages of the chosen methods are discussed.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of Second International Conference on Future Generation Communication and Networking Symposia
ISBN
978-1-4244-3430-5
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
IEEE Computer Society
Place of publication
Los Alamitos
Event location
Sanya
Event date
Dec 13, 2008
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000270432000094