4 papers
Self-Evolving Scientific Agent Discovers Generalizable Physically-Reasoned Fluid Control
Boai Sun, Wenjin Guo, Zongmin Yu +1
While data-intensive deep reinforcement learning can optimize complex control policies, scientific control design in physical systems fundamentally requires an interpretable chain…
Graph In-Context Operator Networks for Generalizable Spatiotemporal Prediction
Chenghan Wu, Zongmin Yu, Boai Sun +1
In-context operator learning enables neural networks to infer solution operators from contextual examples without weight updates. While prior work has demonstrated the effectivenes…
LinguaFluid: Language Guided Fluid Control via Semantic Rewards in Reinforcement Learning
Aoming Liang, Chi Cheng, Dashuai Chen +2
In the domain of scientific machine learning, designing effective reward functions remains a challenge in reinforcement learning (RL), particularly in environments where task goals…
Enhancing Efficiency and Propulsion in Bio-mimetic Robotic Fish through End-to-End Deep Reinforcement Learning
Xinyu Cui, Boai Sun, Yi Zhu +5
Aquatic organisms are known for their ability to generate efficient propulsion with low energy expenditure. While existing research has sought to leverage bio-inspired structures t…