This research develops privacy-preserving, decentralised AI systems where devices learn collaboratively without sharing raw data. Inspired by natural systems like bee colonies, it enables adaptive, self-organising cooperation among devices. The approach improves performance in heterogeneous environments, such as smart cities, while complying with data protection constraints like GDPR.

This research explores swarms of small, modular robots that cooperate like ant colonies to perform complex tasks. Using control theory, optimization, and machine learning, the work enables resilient, energy-efficient robotic systems that adapt in real time, with applications ranging from disaster response and space exploration to medical technologies.