Proposal of a Control Algorithm for Multiagent Cooperation Using Spiking Neural Networks

• Published in: IEEE transaction on neural networks and learning systems Vol. 34; no. 4; pp. 2016 - 2027
• Main Authors: Barton, Adam, Volna, Eva, Kotyrba, Martin, Jarusek, Robert
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.04.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Biological neural networks; Biological system modeling; Computational modeling; Control theory; Cooperation; Firing pattern; Heuristic algorithms; Izhikevich model of a spiking neuron; Mathematical model; multiagent system (MAS); Multiagent systems; Neural networks; Neurons; Proposals; spike timing-dependent plasticity (STDP); Spiking; spiking neural network (SNN)
• ISSN: 2162-237X; 2162-2388; 2162-2388
• DOI: 10.1109/TNNLS.2021.3105800

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.