Deep reinforcement learning (DRL) has emerged as a transformative approach in the realm of fluid dynamics, offering a data-driven framework to tackle the intrinsic complexities of active flow control.

The paper “Deep Reinforcement Learning-based Multi-Objective Scheduling for Distributed Heterogeneous Hybrid Flow Shops with Blocking Constraints,” authored by Xueyan Sun, Weiming Shen, Jiaxin ...

This issue has now been addressed. Li Hang's newly launched book 'Machine Learning Methods (2nd Edition)' dedicates a chapter ...

DeepSeek-R1’s Monday release has sent shockwaves through the AI community, disrupting assumptions about what’s required to achieve cutting-edge AI performance. This story focuses on exactly ...

The development of every field relies on a few foundational classic books, and artificial intelligence is no exception.