Dor Atzmon

Papers

Total Citations

316

H-Index

About

Dor Atzmon is a leading researcher in the field of multi-agent pathfinding (MAPF), a critical area of artificial intelligence focused on coordinating the movement of multiple agents—such as robots or vehicles—without collisions. His most influential work, the 2021 paper "Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks," has garnered 276 citations, establishing a foundational framework for the field by systematically defining problem variants and standardizing benchmarks for evaluation. Atzmon’s contributions extend to practical challenges, as seen in his work on "Multi-Train Path Finding" (20 citations), which adapts MAPF principles to railway systems, and "Safe Multi-Agent Pathfinding with Time Uncertainty" (17 citations), which addresses real-world unpredictability in movement times—a critical issue for autonomous warehouses and traffic control. His recent research on "Conflict-tolerant and conflict-free multi-agent meeting" (2023) explores novel coordination strategies. Atzmon’s work bridges theoretical rigor and applied robotics, offering scalable solutions for complex, dynamic environments. His high-impact publications and focus on safety and uncertainty make him a key figure in advancing autonomous systems, with direct implications for logistics, transportation, and smart infrastructure.