Reinforcement learning (RL) represents a paradigm shift in process control, offering adaptive and data‐driven strategies for the management and optimisation of complex industrial processes. By ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

In just three months, the crew of three young scientists overcame a swarm of challenges to achieve this groundbreaking advancement in robotic autonomy and space operations. “The APIARY team’s ...

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...

UC Santa Cruz’s group of researchers were the winning team of the L2RPN Delft 2023, a competition which invited participants from around the world to use reinforcement learning or similar techniques ...

This system utilizes machine learning algorithms to optimize the operation of particle accelerators, reducing manual intervention and enhancing precision in real-time control. By integrating virtual ...

The study, titled Reinforcement Learning for Monetary Policy Under Macroeconomic Uncertainty: Analyzing Tabular and Function ...