Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...

Among those interviewed, one RL environment founder said, “I’ve seen $200 to $2,000 mostly. $20k per task would be rare but ...

Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...

Request To Download Free Sample of This Strategic Report @- The global reinforcement learning market is experiencing a period of rapid growth, with revenue estimated to increase from approximately $3 ...

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

Using a bunch of carrots to train a pony and rider. (Photo by: Education Images/Universal Images Group via Getty Images) Andrew Barto and Richard Sutton are the recipients of the Turing Award for ...

Forbes contributors publish independent expert analyses and insights. Author, Researcher and Speaker on Technology and Business Innovation. Apr 19, 2025, 03:24am EDT Apr 21, 2025, 10:40am EDT ...

Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...

This article is published by AllBusiness.com, a partner of TIME. What is "Reinforcement Learning"? Reinforcement Learning (RL) is a type of machine learning where a model learns to make decisions by ...

Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...