The Next Web

Everything you need to know about model-free and model-based reinforcement learning

Reinforcement learning is one of the exciting branches of artificial intelligence. It plays an important role in game-playing AI systems, modern robots, chip-design systems, and other applications.
Electronic Design

“Reinforcement Learning” Fuels the Rise of Adaptive Controllers

More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...
VentureBeat

Google researchers improve reinforcement learning by having their AI play Pong

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Deep reinforcement learning — an AI training technique that employs ...
VentureBeat

DeepMind proposes novel way to train ‘safe’ reinforcement learning AI

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Reinforcement learning agents — or AI that’s progressively spurred toward ...
Semiconductor Engineering

DeepSeek: Improving Language Model Reasoning Capabilities Using Pure Reinforcement Learning

“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 ...

Where Reinforcement Learning Plus Human Oversight Works Best

When RL is paired with human oversight, teams can shape how systems learn, correct course when context changes, and ensure ...
EurekAlert!

Reinforcement learning world models for catalyst surface reconstruction: state-of-the-art review

This work presents an AI-based world model framework that simulates atomic-level reconstructions in catalyst surfaces under dynamic conditions. Focusing on AgPd nanoalloys, it leverages Dreamer-style ...
inc42

What Is Reinforcement Learning? Here’s All You Need to Know

Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...