usace.army.mil

Army researchers develop innovative framework for training AI

ADELPHI, Md. — Army researchers developed a pioneering framework that provides a baseline for the development of collaborative multi-agent systems. The framework is detailed in the survey paper ...
EurekAlert!

A new AI-based attack framework advances multi-agent reinforcement learning by amplifying vulnerability and bypassing defenses

Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial ...
Nature

Multi-Agent Reinforcement Learning

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 ...

How Google’s 'internal RL' could unlock long-horizon AI agents

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

Army advances learning capabilities of drone swarms

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 ...
VentureBeat

Meta’s DreamGym framework trains AI agents in a simulated world to cut reinforcement learning costs

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 ...
The Conversation

What is reinforcement learning? An AI researcher explains a key method of teaching machines – and how it relates to training your dog

Ambuj Tewari receives funding from NSF and NIH. Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a ...