Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Traffic congestion, fuel consumption, and emissions also offer quantifiable performance indicators, making mobility uniquely ...
Interesting Engineering on MSN
AI-trained quadruped robot walks rough, low-friction terrain without human input
A quadruped robot has learned to walk across slippery, uneven terrain entirely through simulation, ...
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 ...
A recent study published in Engineering presents a significant advancement in manufacturing scheduling. Researchers Xueyan Sun, Weiming Shen, Jiaxin Fan, and their colleagues from Huazhong University ...
A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and ...
Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...
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