Managing diabetes is a full-time job. But, AI tools are making insulin dosing, glucose tracking, and everyday care a little ...

Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...

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.

Residents on Crews Lake Drive fought against the development on 300 acres, which was previously approved by county staff and ...

Google launched four official and confirmed algorithmic updates in 2025, three core updates and one spam update. This is in comparison to last year, in 2024, where we had seven confirmed updates, then ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks ...

Abstract: This article proposes online data-based reinforcement learning (RL) algorithm for adaptive output consensus control of heterogeneous multiagent systems (MASs) with unknown dynamics. First, ...

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...

Download PDF Join the Discussion View in the ACM Digital Library Deep reinforcement learning (DRL) has elevated RL to complex environments by employing neural network representations of policies. 1 It ...