Dong Jun Kwak
Papers
2
Total Citations
13
H-Index
2
About
Dong Jun Kwak is a researcher specializing in decentralized control, trajectory optimization, and probabilistic game theory, with a focus on multi-agent systems and pursuit-evasion dynamics. His work bridges theoretical foundations and practical algorithms for autonomous decision-making in complex, adversarial environments. Kwak’s most-cited paper, “Decentralized trajectory optimization using virtual motion camouflage and particle swarm optimization” (2014, 7 citations), introduces a novel approach that combines bio-inspired camouflage strategies with swarm intelligence to enable efficient, distributed path planning—offering a scalable solution for coordinating multiple agents without centralized control. In his second highly cited work, “Policy Improvements for Probabilistic Pursuit-Evasion Game” (2013, 6 citations), he advances the understanding of stochastic games by developing improved policies that account for uncertainty in adversarial interactions, enhancing the robustness of autonomous systems in dynamic scenarios. Though his citation counts are modest, Kwak’s contributions are notable for their innovative synthesis of concepts from biology, optimization, and game theory, laying groundwork for future research in autonomous robotics and multi-vehicle coordination. His work remains relevant for students and researchers exploring decentralized intelligence and probabilistic decision-making.
Research Focus
Key Achievements
Top Papers
- 1
- 2Policy Improvements for Probabilistic Pursuit-Evasion Game6 citations · 2013