Roni Stern
Papers
7
Total Citations
484
H-Index
5
About
Roni Stern is a leading researcher in artificial intelligence, with a primary focus on multi-agent pathfinding (MAPF) and heuristic search. His major contributions include foundational work that has shaped the modern understanding and application of MAPF, particularly in large-scale robotics systems like automated warehouses. Stern co-authored the definitive 2021 paper "Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks" (276 citations), which established a standardized framework for the field, and the comprehensive overview "Multi-Agent Path Finding – An Overview" (105 citations). He has also addressed critical real-world challenges, such as planning under time uncertainty and developing bounded-suboptimal search algorithms like Safe Interval Path Planning (SIPP). His work on potential-based bounded-cost search and anytime non-parametric A* has advanced heuristic search theory. With over 480 total citations across his most-cited works, Stern's research directly impacts multi-billion-dollar industries, including Amazon Robotics and Alibaba, by enabling efficient, collision-free coordination of robot fleets. He remains a key voice in identifying future research challenges in multi-agent pickup and delivery problems.
Research Focus
Key Achievements
Top Papers
- 1Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks276 citations · 2021
- 2Multi-Agent Path Finding – An Overview105 citations · 2019
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- 5Safe Multi-Agent Pathfinding with Time Uncertainty17 citations · 2021
- 6Revisiting Bounded-Suboptimal Safe Interval Path Planning5 citations · 2020
- 7What's Hot in Heuristic Search3 citations · 2016