Evolutionary reinforcement learning is an exciting frontier in machine learning, combining the strengths of two distinct approaches: reinforcement learning and evolutionary computation. In ...
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 ...
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 ...
Deepreinforcement learning has disadvantages such as low sample utilization and slow convergence, and thousandsof trial-and-error iterations are required to perform ...
Discover Experiential Reinforcement Learning (ERL), a revolutionary AI training paradigm that allows language models to learn from their own reflections, turning failure into structured wisdom without ...
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 ...
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 ...
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 ...
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