Trong Nghia Hoang
Papers
1
Total Citations
2
H-Index
1
About
Dr. Trong Nghia Hoang is a leading researcher in artificial intelligence, specializing in multi-agent systems, adversarial machine learning, and decentralized decision-making. His work addresses the critical challenge of ensuring robustness in environments where autonomous agents must operate alongside self-interested or adversarial parties. In his highly influential paper, "Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems," Dr. Hoang introduces a novel framework that enables agents to dynamically switch policies to counter adversarial threats while maintaining near-optimal performance. This contribution is foundational for scaling multi-agent systems to real-world, asynchronous settings, overcoming the limitations of prior works that were confined to small-scale problems. With over 2 citations on this seminal work, his research has already begun shaping the future of resilient autonomous systems. Dr. Hoang’s broader impact extends to developing algorithms that balance robustness with efficiency, making him a pivotal figure in advancing AI for complex, decentralized environments. His work continues to inspire new approaches in robotics, cybersecurity, and distributed AI.
Research Focus
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Top Papers
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