Holonic Learning

Holonic learning is a distributed machine learning framework that organizes learning agents, called holons, into a hierarchical structure to collaboratively train models. Current research focuses on applying this architecture to improve efficiency and address privacy concerns in diverse applications, such as coordinating robots and humans in manufacturing and enhancing communication in complex systems using natural language processing. This approach offers advantages in handling large datasets and non-uniform data distributions, demonstrating potential for improved scalability and robustness in machine learning.