Electronics360

Wind turbine control systems: From PID to reinforcement learning

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...
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 ...
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 ...
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 ...
Analytics India Magazine

Complex Reinforcement Learning Tasks Can Cost Up to $20,000 Each: EpochAI Report

Among those interviewed, one RL environment founder said, “I’ve seen $200 to $2,000 mostly. $20k per task would be rare but ...
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 ...