GitHub

Train multi-step agents for real-world tasks using GRPO.

RULER (Relative Universal LLM-Elicited Rewards) eliminates the need for hand-crafted reward functions by using an LLM-as-judge to automatically score agent trajectories. Simply define your task in the ...
MilitaryNews.com

Reinforcement learning is making a buzz in space

A (NRL) research team successfully conducted the first reinforcement learning (RL) control of a free-flyer in space on May 27 ...

We Finally Know How Much It Cost to Train China’s Astonishing DeepSeek Model

DeepSeek found that it could improve the reasoning and outputs of its model simply by incentivizing it to perform a trial-and ...
Tech Xplore

The AI model that teaches itself to think through problems, no humans required

Artificial intelligence is getting smarter every day, but it still has its limits. One of the biggest challenges has been ...
IEEE

ALARM: Safe Reinforcement Learning With Reliable Mimicry for Robust Legged Locomotion

Abstract: Legged robots are supposed to traverse complicated environments, which makes it challenging to design a model-based controller due to their functional complexity. Currently, using deep ...

Researchers Propose a Novel Representation Learning Framework to Address the Lack of Causal Characterization in Deep Learning Models

Recently, researchers introduced a new representation learning framework that integrates causal inference with graph neural networks—CauSkelNet, which can be used to model the causal relationships and ...
The Debrief

US Navy Scientists Teach Zero-Gravity Robot to Fly in Space Without Human Interference

US Naval Research Laboratory scientists have successfully trained an Astrobee zero-gravity robot to fly in space without human interference.
IEEE

Hybrid Reinforcement Learning for Joint Beamforming in STAR-RIS-Assisted CoMP Systems

Abstract: The simultaneously transmitting and reflecting reconfigurable intelligent surface(STAR-RIS) can provide a full-coverage agile radio environment. A unique ...