학술논문

Proposal of a Control Algorithm for Multiagent Cooperation Using Spiking Neural Networks
Document Type
Periodical
Source
IEEE Transactions on Neural Networks and Learning Systems IEEE Trans. Neural Netw. Learning Syst. Neural Networks and Learning Systems, IEEE Transactions on. 34(4):2016-2027 Apr, 2023
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
General Topics for Engineers
Neurons
Mathematical model
Computational modeling
Biological neural networks
Biological system modeling
Heuristic algorithms
Proposals
Izhikevich model of a spiking neuron
multiagent system (MAS)
spiking neural network (SNN)
spike timing-dependent plasticity (STDP)
Language
ISSN
2162-237X
2162-2388
Abstract
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.