Proposal of a Control Algorithm for Multiagent Cooperation Using Spiking Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F21%3AA2202C3F" target="_blank" >RIV/61988987:17310/21:A2202C3F - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9524456" target="_blank" >https://ieeexplore.ieee.org/document/9524456</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TNNLS.2021.3105800" target="_blank" >10.1109/TNNLS.2021.3105800</a>
Alternative languages
Result language
angličtina
Original language name
Proposal of a Control Algorithm for Multiagent Cooperation Using Spiking Neural Networks
Original language description
The study deals with the issue of using spiking neural networks (SNNs) in multiagent systems. The research objective is a proposal of a control algorithm for the cooperation of a group of agents using SNNs, application of the Izhikevich model, and plasticity depending on the timing of action potentials. The proposed method has been verified and experimentally tested, proving numerous advantages over second-generation networks. The advantages and the application in real systems are described in the research conclusions.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Neural Networks and Learning Systems
ISSN
2162-237X
e-ISSN
2162-2388
Volume of the periodical
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Issue of the periodical within the volume
August 2021
Country of publishing house
US - UNITED STATES
Number of pages
12
Pages from-to
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UT code for WoS article
000732331700001
EID of the result in the Scopus database
2-s2.0-85114595827