(THE CONVERSATION) Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a cornerstone of intelligence for ...

Evaluating the advantages and potential drawbacks of shielding as a method for safe RL. Bettina Könighofer is an assistant ...

Machine learning, a branch of artificial intelligence, allows a computer to teach itself how to solve problems by analyzing ...

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.

This is reinforcement learning (RL), arguably the biggest driver of AI progress over the past six months and getting more intricate all the time. You can do reinforcement learning with human graders, ...

By teaching models to reason during foundational training, the verifier-free method aims to reduce logical errors and boost ...

For a long time, the core idea in reinforcement learning (RL) was that AI agents should learn every new task from scratch, like a blank slate. This "tabula rasa" approach led to amazing achievements, ...

“We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT ...