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 ...

Google finds that AI agents learn to cooperate when trained against unpredictable opponents

Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — ...
Insurancenewsnet.com

Reports from University of Central Florida Add New Data to Findings in Risk Management (Multi-objective Reinforcement Learning Approach for Improving Safety At Intersections ...

2020 SEP 28 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News-- Data detailed on Risk Management have been presented. According to news originating from Orlando, Florida, by ...
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 ...
CU Boulder News & Events

Christopher Sullivan

Christopher Sullivan is a fifth-year Ph.D. student under Dr. Natasha Bosanac at the University of Colorado Boulder. His research leverages multi-objective reinforcement learning to explore the ...
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 ...
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 ...
EurekAlert!

Optimal multi-impulse linear rendezvous via reinforcement learning

First, authors provide the mathematical model describing a multi-impulse linear rendezvous problem and the RL algorithms used, and present the RL-based approach to rendezvous design. For the ...