Resilient Decision-Making for Multi-Robot Systems in the Presence of Adversaries

This talk presents a unified perspective on resilient decision-making for multi-robot systems in environments where adversaries may influence routing, search, and detection tasks. Recently, significant progress in coordination, control, and navigation of multi-robot systems has been achieved, driven primarily by the rapid commercialization of unmanned aerial systems and drones. Yet, real-world deployment remains challenging. Most research assumes cooperative or optimally performing agents, overlooking adversarial or suboptimal behavior due to uncertainty, faults, or environmental disturbances. Resilience to malicious or malfunctioning agents remains a key limitation, as such agents can degrade efficiency and destabilize routing policies, where stability is defined as bounded cost over time. Existing stability guarantees for cooperative fleets collapse when agents deviate from plans, underscoring the need for adversarially aware planning and routing theory in safety-critical applications.

I will present new theoretical and experimental results on resilient multi-agent policies for coordination, control, and learning under uncertainty and adversarial influence, focusing on routing and traffic management for fleets of aerial and ground agents for which I develop adaptive algorithms that provide provable stability, resilience, and safety guarantees. Finally, I will show how resilient cooperative search strategies address challenges posed by intelligent, coordinated external adversaries, providing provable guarantees for coverage and detection in settings such as search and rescue and pursuit-evasion. I conclude by outlining future research directions at the intersection of safety, learning, and large-scale autonomy with Urban Air Mobility serving as a compelling application.

Bio:

Roee M. Francos is currently a Computer Science Postdoctoral Fellow at the Robotics, Embedded Autonomy, and Communication Theory (REACT) Lab at Harvard University working with Prof. Stephanie Gil, focusing on development of multi-agent resilient decision-making and coordination algorithms. In 2023, he completed his PhD in Computer Science under supervision of Prof. Freddy Bruckstein, at the Technion-Israel Institute of Technology. He received the B.Sc. in Electrical and Computer Engineering from Ben-Gurion University. His research interests are in multi-agent teamwork, autonomous robotics, intelligent transportation systems, bio-inspired robotics and computer vision, focusing on collaborative algorithms for motion planning of autonomous vehicles, multi-robot learning , and air traffic management and coordination of unmanned vehicles. Roee is a recipient of the 2023 Robotics Science and Systems (RSS) Pioneers Award and the 2025 IEEE Multi-Robot & Multi-Agent Systems (MRS) Young Pioneer Award.