Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...
In June 2021, scientists at the AI lab DeepMind made a controversial claim. The researchers suggested that we could reach artificial general intelligence (AGI) using one single approach: reinforcement ...
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How the Brain Uses Reinforcement Learning Beyond Just Mean Rewards
What if our brains learned from rewards not just by averaging them but by considering their full range of possibilities? A ...
THESE DROIDS HOW TO FUNCTION. RIGHT NOW, WE ARE STEPPING BACK INTO THE FUTURE WITH A RARE LOOK INSIDE THE ROBOTICS INSTITUTE AT CMU. THE WORK BEING INVENTED RIGHT HERE IN PITTSBURGH WILL HAVE A MAJOR ...
Ambuj Tewari receives funding from NSF and NIH. Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a ...
The idea of reinforcement learning—or learning based on reward—has been around for so long it’s easy to forget we don’t really know how it works. If DeepMind’s new bombshell paper in Nature is any ...
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 ...
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