Robotics is entering a new phase where general-purpose learning matters as much as mechanical design. Instead of programming ...
Microsoft and Tsinghua University have developed a 7B-parameter AI coding model that outperforms 14B rivals using only ...
MemRL separates stable reasoning from dynamic memory, giving AI agents continual learning abilities without model fine-tuning ...
"Welcome to the world of RDHNet, a groundbreaking approach to multi-agent reinforcement learning (MARL) introduced by Dongzi Wang and colleagues from the College of Computer Science at the National ...
Precipitation and cold temperatures are forecasted for Saturday, Sunday and Monday, with an ice storm possible for Sunday.
Rebecca Qian is the Co-Founder and CTO of Patronus AI, with nearly a decade of experience building production machine ...
Abstract: With extensive pretrained knowledge and high-level general capabilities, large language models (LLMs) emerge as a promising avenue to augment reinforcement learning (RL) in aspects, such as ...
HybridLeg robots Olaf and Snogie use impact-safe design and self-recovery to enable scalable, real-world hardware ...
Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Dopamine under control: Precision regulation of inhibition shapes learning, memory and mental health
For decades, dopamine has been celebrated in neuroscience as the quintessential "reward molecule"—a chemical herald of ...
FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.
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