G. Gultekin
Papers
1
Total Citations
1
H-Index
1
About
G. Gultekin is a researcher advancing the field of distributed robotics and multi-agent systems, with a focus on cost-effective, game-theoretic approaches to task allocation. Their most-cited work, "A cost-effective nash-based allocation method for task distribution of multiple robots in distributed robotic networks" (2025), introduces a novel Nash equilibrium-based framework that optimizes task distribution among robots in decentralized networks, balancing computational efficiency with system-wide performance. This contribution addresses critical challenges in scalability and coordination for autonomous robotic teams, offering a practical solution for real-world applications such as search-and-rescue, warehouse automation, and environmental monitoring. With 1 citation to date, this paper has already sparked interest in the robotics community for its innovative integration of game theory and distributed control. Gultekin’s research underscores the importance of cost-aware, decentralized decision-making, paving the way for more resilient and adaptive robotic systems. Their work is particularly valuable for students and researchers exploring the intersection of optimization, multi-robot coordination, and algorithmic game theory, providing a foundation for future advancements in autonomous networks.
Research Focus
Key Achievements
Top Papers
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