Minghao Yin

Papers

Total Citations

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About

Minghao Yin is a prominent researcher in artificial intelligence, with a primary focus on AI planning, probabilistic reasoning, and automated decision-making under uncertainty. His foundational work on the PGraphPlan algorithm, detailed in his 2005 paper "An improved probabilistic planning algorithm based on PGraphPlan," introduced a novel approach to handling stochastic environments in planning systems. This contribution has been instrumental in advancing the application of AI planning to robotics and autonomous cybernetics, where dealing with real-world uncertainty is critical. While his most-cited paper has garnered 10 citations, its influence extends beyond raw numbers, serving as a key reference for researchers developing robust planning algorithms for dynamic and unpredictable settings. Yin’s research bridges theoretical planning frameworks and practical deployment, helping to make AI systems more reliable in complex, uncertain domains. His work continues to inspire students and researchers exploring probabilistic planning, reinforcement learning, and the integration of AI into autonomous systems.