\paper
{Multi-Agent Systems for Intelligent Disaster Response and Resource Allocation}
{Kasun Perera, Nadeesha Silva, Dinuka Fernando, Tharindu Jayasinghe}
{Kasun Perera$^{1}$, Nadeesha Silva$^{1}$, Dinuka Fernando$^{2}$, Tharindu Jayasinghe$^{3}$}
{$^{1}$Faculty of Computing, University of Sri Jayewardenepura, Sri Lanka\\
	$^{2}$Department of Information Technology, University of Moratuwa, Sri Lanka\\
	$^{3}$Department of Computer Science, University of Colombo, Sri Lanka\\
	Email: kasun@sjp.ac.lk}
{Natural disasters such as floods, earthquakes, and landslides present significant challenges for timely response and efficient resource allocation. Traditional disaster management systems often suffer from delays, lack of coordination, and inefficient utilization of available resources. This study proposes a multi-agent system (MAS) framework to enhance intelligent disaster response through decentralized decision-making and real-time coordination among autonomous agents.
	
	The proposed system models disaster response entities such as emergency services, rescue teams, and resource distribution units as intelligent agents. Each agent operates independently while communicating with other agents using predefined protocols to share information and coordinate actions. The system integrates real-time data from sensors, geographic information systems (GIS), and communication networks to support dynamic decision-making. Machine learning techniques are incorporated to predict resource demand and optimize allocation strategies during emergency situations.
	
	A simulation environment is developed to evaluate the effectiveness of the proposed MAS framework under various disaster scenarios. Experimental results indicate that the system significantly improves response time, enhances coordination among response units, and ensures more efficient utilization of critical resources compared to centralized approaches. The system also demonstrates scalability and adaptability to different types of disasters and geographical conditions.
	
	Furthermore, this study discusses challenges such as communication reliability, system robustness, and ethical considerations related to decision-making in critical situations. The findings highlight the potential of multi-agent systems in transforming disaster management practices and improving resilience in affected communities.
	
	\textbf{Keywords:} Multi-Agent Systems, Disaster Management, Resource Allocation, Intelligent Systems, Emergency Response
}