You might have seen headlines sounding the alarm about the safety of an emerging technology called agentic AI.

Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...

Researchers at Meta, the University of Chicago, and UC Berkeley have developed a new framework that addresses the high costs, infrastructure complexity, and unreliable feedback associated with using ...

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...

With the Nemotron 3 family of models, developers can choose the open model that is right-sized for their specific workloads, scaling from dozens to hundreds of agents while benefiting from faster, ...

ADELPHI, Md. -- Army researchers developed a reinforcement learning approach that will allow swarms of unmanned aerial and ground vehicles to optimally accomplish various missions while minimizing ...

Patronus AI unveiled “Generative Simulators,” adaptive “practice worlds” that replace static benchmarks with dynamic ...