Smart City Gnosys

Smart city article details

Title Swarm Intelligence Decentralized Decision Making In Multi-Agent System
ID_Doc 54132
Authors Joseph A.A.; Nambiar G.S.; Jayapandian N.
Year 2023
Published Proceedings of the 8th International Conference on Communication and Electronics Systems, ICCES 2023
DOI http://dx.doi.org/10.1109/ICCES57224.2023.10192625
Abstract This research aims to understand how groups of agents can make decisions collectively without relying on a central authority. The research could focus on developing algorithms and models for distributed problem solving, such as consensus-reaching and voting methods, or for coordinating actions among agents in a decentralized manner. The research could also look into the application of these methods in various fields like distributed robotics, swarm intelligence, and multi-agent systems in smart cities and transportation networks. Swarm intelligence in decentralization is an emerging field that combines the principles of swarm intelligence and decentralized systems to design highly adaptive and scalable systems. These systems consist of a large number of autonomous agents that interact with each other and the environment through local communication and adapt their behaviors based on environmental cues. The decentralized nature of these systems makes them highly resilient and efficient, with potential applications in areas such as robotics, optimization, and block chain technology. However, designing algorithms and communication protocols that enable effective interaction among agents without relying on a centralized controller remains a key challenge. This article proposes a model for swarm intelligence in decentralization, including agents, communication, environment, learning, decision-making, and coordination, and presents a block diagram to visualize the key components of the system. The paper concludes by highlighting the potential benefits of swarm intelligence in decentralization and the need for further research in this area. © 2023 IEEE.
Author Keywords Artificial Intelligence; Blockchain; Decentralize; Multi -agent; Optimization; Swarm Intelligence


Similar Articles


Id Similarity Authors Title Published
17700 View0.882Rizk Y.; Awad M.; Tunstel E.W.Decision Making In Multiagent Systems: A SurveyIEEE Transactions on Cognitive and Developmental Systems, 10, 3 (2018)
54131 View0.874Zedadra O.; Guerrieri A.; Jouandeau N.; Spezzano G.; Seridi H.; Fortino G.Swarm Intelligence And Iot-Based Smart Cities: A ReviewInternet of Things (2019)
14763 View0.874Mirza N.M.; Ali A.; Shifa N.; Ishak M.K.; Ammar K.; Mohd Yusof S.A.Collective Intelligence Unleashed: Exploring The Dynamics And Applications Of Swarm Robotic SystemsProceedings of the International Conference on Automation, Robotics and Applications, ICARA, 2025 (2025)
16204 View0.857Qin C.; Pournaras E.Coordination Of Drones At Scale: Decentralized Energy-Aware Swarm Intelligence For Spatio-Temporal SensingTransportation Research Part C: Emerging Technologies, 157 (2023)
23567 View0.855Aguzzi G.; Savaglio C.Engineering Distributed Collective Intelligence In Cyber-Physical SwarmsProceedings - 2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2024 (2024)
5124 View0.854Nezamoddini N.; Gholami A.A Survey Of Adaptive Multi-Agent Networks And Their Applications In Smart CitiesSmart Cities, 5, 1 (2022)