Noa Agmon

Noa Agmon is a computer scientist whose AI research examines coordination in multi-robot and multi-agent systems. Her early work includes fault-tolerant robot gathering, cooperative multi-robot systems, and patrol under complex conditions. She co-chairs ECAI’s workshop program in 2024. In 2025, EurAI elects her a Fellow as she coauthors papers on coalition learning and graph neural networks and co-chairs AAAI’s demonstration program. As of October 2026, she is a professor at Bar-Ilan University and gives a talk on strategic robot teams and swarms at Ben-Gurion University.

Now at: Bar-Ilan University
Works: 155
Citations: 2,206
h-index: 25
Badges: Loyal

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

2004

Fault-tolerant robot gathering

In 2004, she coauthors the SODA paper “Fault-tolerant gathering algorithms for autonomous mobile robots” with David Peleg.
2008

Cooperative multi-robot thesis

At AAMAS in 2008, her doctoral project is titled “Models and Algorithmic Approaches for Cooperative Multi-Robot Systems.”
2011

Patrol under complex conditions

At the University of Texas at Austin, she coauthors the 2011 paper “Multiagent Patrol Generalized to Complex Environmental Conditions.” The paper studies patrol where environmental conditions change travel costs and gives a heuristic that improves visit frequency.
2024

ECAI workshop chair

In 2024, she co-chairs ECAI’s workshop program with Michela Milano.
2025

A EurAI Fellowship

EurAI elects her a Fellow in 2025 for contributions to multi-agent systems and strategic modeling in multi-robot systems. With Saar Cohen, she coauthors “Online Learning of Coalition Structures by Selfish Agents,” which proposes a sample-efficient algorithm for selfish agents. She also co-chairs AAAI-25’s demonstration program.
2025

Decentralized coalition learning

With Saar Cohen, she coauthors “Decentralized Online Learning by Selfish Agents in Coalition Formation” for IJCAI 2025. The paper develops a sample-efficient decentralized algorithm that aims to reduce Nash regret and produce approximately Nash-stable solutions.
2025

Convexified graph neural networks

With Saar Cohen and Uri Shaham, she coauthors “Convexified Message-Passing Graph Neural Networks.” The framework casts GNN training as convex optimization and establishes generalization guarantees for two-layer models.
As of October 2026

Professor at Bar-Ilan

As of October 2026, she is a professor at Bar-Ilan University. In October 2026, she presents “Strategic Robots: Between Cooperation and Competition in Robot Teams and Swarms” at Ben-Gurion University’s National Conference on Computer and Information Sciences.