Network Selection

Network selection encompasses the automated choice of the optimal network or resource for a given task, aiming to maximize efficiency and performance while minimizing costs or resource consumption. Current research focuses on developing sophisticated selection mechanisms using diverse approaches, including reinforcement learning, graph neural networks, and large language models, often integrated within larger architectures like selector-predictor models or multi-agent systems. These advancements have significant implications across various fields, improving efficiency in areas such as robotic navigation, image processing, and federated search, as well as enabling more robust and adaptable systems in resource-constrained environments.