Crowd Panic Behavior Simulation Using Multi-Agent Modeling

This research introduces a novel approach to crisis management by implementing a multi-agent algorithm within a strategic decision system. The proposed system harnesses multiple agents’ collective intelligence and adaptive capabilities to enhance decision-making processes during critical situations....

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Bibliographic Details
Published in:Electronics (Basel) 2024-09, Vol.13 (18), p.3622
Main Authors: Dumitrescu, Cătălin, Radu, Valentin, Gheorghe, Radu, Tăbîrcă, Alina-Iuliana, Ștefan, Maria-Cristina, Manea, Liliana
Format: Article
Language:English
Subjects:
Adaptive algorithms
Adaptive systems
Algorithms
Analysis
Artificial intelligence
Behavior
Communication
Crisis management
Decision making
Evacuation of civilians
Evacuation routing
Harnesses
Information systems
Multiagent systems
Resource allocation
Romania
Simulation
Simulation methods
Swarm intelligence
Trouble shooting
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Summary:This research introduces a novel approach to crisis management by implementing a multi-agent algorithm within a strategic decision system. The proposed system harnesses multiple agents’ collective intelligence and adaptive capabilities to enhance decision-making processes during critical situations. The study first investigates the theoretical foundations of crisis management and multi-agent systems, emphasizing the need for an integrated approach that combines strategic decision-making with autonomous agents. Subsequently, the research presents the design and implementation of the multi-agent algorithm, outlining its ability to gather, process, and analyze diverse data sources in real time. The multi-agent algorithm is specifically tailored to adapt to dynamic crisis scenarios, ensuring a resilient decision-making framework. Experimental simulations present the implementation of a panic simulator and prediction of evacuation and intervention routes using multi-agent artificial intelligence algorithms. The results demonstrate the multi-agent algorithm-driven decision system’s superiority in response time, resource allocation, and overall crisis mitigation. Furthermore, the research explores the system’s scalability and adaptability to different crisis types, illustrating its potential applicability across diverse domains.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics13183622