Prof. Noa Agmon
Prof. Noa Agmon develops algorithms that enable multi-robot systems to make decentralized decisions, finding the optimal balance between collective teamwork and the independent action of each robot.
CV
Prof. Agmon holds an M.Sc. from the Weizmann Institute of Science and a Ph.D. with honors from Bar-Ilan University. Following post-doctoral fellowships at the Weizmann Institute and the University of Texas at Austin, she established the SMART (Swarm Multi-Agent and Robot Teams) Lab at Bar-Ilan. She is a Fellow of EurAI and is actively involved in national and international projects in the field of autonomous systems.
Research
Robotics, Multi-Agent Systems, and AI
A group of drones scans a disaster zone after an earthquake to locate survivors — autonomous robots operating together in a complex environment. Each drone has limited battery life, the terrain is filled with dynamic obstacles, and there is no central controller to coordinate the mission. In such a reality, success depends on the robots' ability to divide the area, patrol efficiently, and adapt to changes in real-time — without relying on external control.
Prof. Noa Agmon develops algorithms that enable multi-robot systems to make decentralized decisions, finding the optimal balance between collective teamwork and the independent action of each robot. Her research combines algorithmic development with theoretical analysis, translating mathematical models into practical applications — from autonomous drones to smart infrastructures.
Key Research Areas:
Swarm Robotics & Decentralized Decision-Making: Coordinating large groups of autonomous agents.
Patrol, Coverage & Navigation: Optimizing movement and monitoring in complex terrains.
Multi-Agent Systems: Analyzing the balance between cooperation and competition.
Learning under Uncertainty: Developing robust strategies for unpredictable environments.
Research Nature:
Theoretical-Applied: Developing algorithms with provable optimality, alongside simulations and real-world robotic systems.
Career Paths:
Graduates of the lab transition into diverse high-level roles:
Industry: Algorithm Engineers and Autonomous Systems Developers in robotics and tech companies.
Academia: Researchers and lecturers in AI and robotics fields.
Entrepreneurship: Developers of AI-based solutions for decentralized and autonomous systems.
Last Updated Date : 19/07/2026
