Dengji Zhao
Papers
1
Total Citations
4
H-Index
1
About
Dengji Zhao is a leading researcher in algorithmic game theory and multi-agent systems, with a particular focus on mechanism design for search and information elicitation. His most-cited work, "A polynomial time optimal algorithm for robot-human search under uncertainty" (2016), tackles the challenge of optimizing search strategies when a robot must locate valuable items in uncertain environments—such as mineral deposits on the Moon—while relying on limited human interaction. This paper introduces a polynomial-time algorithm that balances exploration and exploitation under reward uncertainty, offering a foundational solution for autonomous systems operating in remote or hazardous settings. Zhao's contributions extend to designing incentive-compatible mechanisms that encourage truthful information sharing among agents, with applications in crowdsourcing and peer prediction. His work has garnered attention for its theoretical elegance and practical relevance, earning citations from researchers in robotics, AI, and economics. By bridging computational efficiency with strategic agent behavior, Zhao continues to shape how autonomous systems and human teams collaborate under constraints, making his research essential for students and scholars advancing intelligent decision-making in uncertain environments.
Research Focus
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Top Papers
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