Multi User

Multi-user systems research focuses on designing and optimizing systems that effectively handle interactions and resource allocation among multiple users, addressing challenges arising from diverse user needs and limited resources. Current research emphasizes developing algorithms and models, such as deep reinforcement learning and graph neural networks, to manage these complexities in various applications, including collaborative decision-making, resource allocation in edge computing, and personalized service delivery. This field is significant because it improves efficiency, personalization, and security in diverse areas like communication networks, machine learning, and human-computer interaction, leading to more robust and user-friendly systems.