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 ...
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 ...
EurekAlert!

Deep-reinforcement-learning-based robot motion strategies for grabbing objects from human hands

Deepreinforcement learning has disadvantages such as low sample utilization and slow convergence, and thousandsof trial-and-error iterations are required to perform ...
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 ...
Forbes

Artificial Intelligence: What Is Reinforcement Learning - A Simple Explanation & Practical Examples

At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward. Similar to toddlers learning how to walk who adjust actions based on the ...