Herding Algorithm

Herding algorithms encompass a range of techniques inspired by collective animal behavior, aiming to guide or influence a group of entities towards a desired outcome. Current research focuses on improving the efficiency and robustness of these algorithms, particularly within recommendation systems, where "herding effects" (biased user feedback) pose a challenge, and in federated learning, where selecting beneficial data subsets is crucial. These algorithms find applications in diverse fields, from optimizing online recommendations and accelerating machine learning to improving AI safety and even enhancing pedestrian safety through route optimization.