Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Researchers in the US developed bipedal robots with a new design, the HybridLeg platform, ...
Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...
Reinforcement learning algorithms help AI reach goals by rewarding desirable actions. Real-world applications, like healthcare, can benefit from reinforcement learning's adaptability. Initial setup ...
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 ...
Among those interviewed, one RL environment founder said, “I’ve seen $200 to $2,000 mostly. $20k per task would be rare but ...
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 ...
Multi-Objective Reinforcement Learning (MORL) is an emerging field that extends the conventional reinforcement learning paradigm by enabling agents to optimise multiple conflicting objectives ...
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 ...
David Silver is responsible for several eye-catching demonstrations of artificial intelligence in recent years, working on advances that helped revive interest in the field after the last great AI ...
Someone looking to book a vacation online today might have very different preferences than they did before the COVID-19 pandemic. Instead of flying to an exotic beach, they might feel more comfortable ...