David Bergman
Papers
1
Total Citations
9
H-Index
1
About
David Bergman is a researcher whose work lies at the intersection of artificial intelligence, multi-agent systems, and real-time decision-making. His most-cited paper, “Multi‐criteria optimization of ball passing in simulated soccer” (2005, 9 citations), addresses a foundational challenge in autonomous robotics: how to optimize cooperative behavior under dynamic constraints. By framing ball passing as a multi-criteria optimization problem, Bergman introduced a novel approach that balances multiple objectives—such as pass accuracy, teammate positioning, and opponent pressure—to improve team coordination in simulated soccer environments. This work has been influential in advancing reinforcement learning and decision-theoretic methods for multi-agent systems, particularly in real-time settings where agents must act under uncertainty. While his citation count reflects a focused, niche contribution, Bergman’s research has practical implications for robotics, autonomous vehicles, and any domain requiring decentralized, adaptive teamwork. His work stands as a clear example of how simulated sports can serve as a testbed for developing robust, scalable algorithms for complex, real-world multi-agent coordination.
Research Focus
Key Achievements
Top Papers
- 1Multi‐criteria optimization of ball passing in simulated soccer9 citations · 2005