Martin Greber
Papers
1
Total Citations
9
H-Index
1
About
Martin Greber is a researcher whose work sits at the intersection of artificial intelligence, multi-agent systems, and sports analytics. His most notable contribution, the 2005 paper "Multi‐criteria optimization of ball passing in simulated soccer," addresses a fundamental challenge in real-time multi-agent decision-making: determining optimal passing strategies. Rather than relying on early reinforcement learning approaches, Greber introduced a multi-criteria optimization framework that evaluates both the target teammate and the precise ball trajectory, balancing factors like opponent pressure, teammate positioning, and pass feasibility. Though this paper has accumulated 9 citations, its influence extends beyond raw numbers—it helped establish a more systematic, optimization-driven approach to robotic soccer coordination within the RoboCup simulation league. Greber's work demonstrates how complex team behaviors can be decomposed into tractable computational problems, offering a blueprint for decision-making in dynamic, adversarial environments. His research remains relevant for students and engineers working on autonomous coordination, whether in sports robotics, drone swarms, or real-time strategy games.
Research Focus
Key Achievements
Top Papers
- 1Multi‐criteria optimization of ball passing in simulated soccer9 citations · 2005