The core idea behind reinforcement learning is for a system to learn in the same manner that people and animals learn—by ...

Research team from Nanjing University proposed FOCUS, a causal model-based offline RL algorithm, which uses causal structure ...

Beyond high performance, the RL framework’s main advantage lies in its real-time application potential. Once trained, the ...

In this modern era, Reinforcement Learning (RL) has evolved from theoretical research to a transformative force driving significant changes in industrial applications. Debu Sinha, a recognized ...

Research team introduced clustered reinforcement learning (CRL), a novel RL framework for efficient exploration in large state spaces or sparse ...

One of the researchers highlighted three subjects students should study for technical depth.

These early iterations relied heavily on observed learning, where historical data – both malicious and benign – was fed to ...

Prime Intellect has released INTELLECT-2, a 32 billion parameter language model trained using fully asynchronous ...

The latest addition is the Phi-4 Reasoning — a 14 billion-parameter model built by applying a supervised fine-tuning (SFT) algorithm to the Phi-4 base model. The researchers also derived the Phi-4 ...

Animal research has always walked a tightrope between necessity and controversy. It has yielded critical breakthroughs in ...

A new generation of enterprise security frameworks is being developed–one that reacts to threats in real-time. Hassan Rehan, ...