Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
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 ...
Traffic congestion, fuel consumption, and emissions also offer quantifiable performance indicators, making mobility uniquely ...
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AI-trained quadruped robot walks rough, low-friction terrain without human input
This multi-objective setup encourages natural walking behavior rather than rigid or inefficient movement. A four-stage ...
Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...
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 ...
Have you ever wished AI could truly understand the complexities of your field—not just replicate data but reason through intricate, domain-specific challenges? Whether you’re a researcher analyzing ...
In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...
A new machine learning approach that draws inspiration from the way the human brain seems to model and learn about the world has proven capable of mastering a number of simple video games with ...
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