Portrait of Zhaoyang Yu

Zhaoyang Yu

DeepWisdom

I am a Research Intern at DeepWisdom, where I work with Chenglin Wu, Jiayi Zhang, and Yifan Wu. I am fortunate to collaborate with Bang Liu and Yuyu Luo.

I received my B.E. from the Renmin University of China. As a Co-Founder of OpenManus and a member of Foundation Agents, I am committed to advancing open-source agent infrastructure and research. Currently, my research interest focuses on developing LLM-based agents that can operate effectively across diverse environments and tasks.

Focus

  • Agent learning. Learning is key to cross-environment capabilities. Learning environment dynamics requires complex optimization approaches, signals, and targets beyond model parameters, like AFlow optimizing decision workflows and SPO exploring new reward signals for prompt optimization.
  • Decision-making. Human decision-making naturally enables cross-environment learning and generalization. We explore agent decision structures that mirror human reasoning, potentially unlocking similar learning advantages. AoT atomizes reasoning to address context limitations, while ReCode unifies planning and action for more natural decision-making.
  • Environment scaling. Agent environments are inevitably simplified versions of human environments, lacking complexity, dynamics, and rich reward signals that make agent learning inherently challenging. We aim to scale environments to provide richer dynamics, diverse distributions, and more abundant rewards for effective learning.

I am actively seeking a PhD position.

Selected Publications

Selected Projects

Experience

Service

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