EurekAlert!

Multi-objective deep reinforcement learning strategy paves the way for safer, greener autonomous electric mobility

The rapid rise of electric vehicles combined with breakthroughs in autonomous driving technology is reshaping the future of ...
Nature

Multi-Objective Reinforcement Learning

Multi-Objective Reinforcement Learning (MORL) is an emerging field that extends the conventional reinforcement learning paradigm by enabling agents to optimise multiple conflicting objectives ...
FedScoop

The Army looks to pave way for autonomous vehicles with new AI research

U.S. Army paratroopers assigned to Bravo Company, 54th Brigade Engineer Battalion, 173rd Airborne Brigade prepare the Dragon Runner 10 robot for operation in Grafenwoehr Training Area during the 2019 ...
EurekAlert!

Evolutionary reinforcement learning promises further advances in machine learning

Evolutionary reinforcement learning is an exciting frontier in machine learning, combining the strengths of two distinct approaches: reinforcement learning and evolutionary computation. In ...
Semiconductor Engineering

Thermally-Aware, Multi-Objective Scheduling Framework for DL Workloads on Heterogeneous Multi-Chiplet PIM Architectures (UW–Madison, Washington State)

A new technical paper titled “THERMOS: Thermally-Aware Multi-Objective Scheduling of AI Workloads on Heterogeneous Multi-Chiplet PIM Architectures” was published by researchers at the University of ...
MIT Technology Review

Reinforcement Learning

Progress in self-­driving cars and other forms of automation will slow dramatically unless machines can hone skills through experience. Inside a simple computer simulation, a group of self-driving ...
Forbes

From Turing To DeepSeek, Reinforcement Learning Soars To AI Summit

Using a bunch of carrots to train a pony and rider. (Photo by: Education Images/Universal Images Group via Getty Images) Andrew Barto and Richard Sutton are the recipients of the Turing Award for ...