Abstract: Power systems are well-engineered systems designed to supply power generation and services to end users. They are considered as the most crucial infrastructures in modern societies as ...
The third-ranking leader in the House of Representatives, who also happens to hail from Minnesota, demanded answers from Gov. Tim Walz after a YouTuber tried to confront employees of an alleged ...
Abstract: The sparse reward problem widely exists in multi-agent deep reinforcement learning, preventing agents from learning optimal actions and resulting in inefficient interactions with the ...
AgiBot announced a key milestone this week with the successful deployment of its Real-World Reinforcement Learning system in a manufacturing pilot with Longcheer Technology. The pilot project marks ...
Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...
Parents visiting their children’s kindergarten class for the first time may think they’ve arrived at the wrong room, especially if they expect it to resemble the kindergarten they attended as ...
Co-authored by Xiaoyan Dong, Hannah Farrell, and Michael Hogan. Artificial intelligence (AI) is rapidly changing how we learn and develop knowledge and skills. With the development of AI, more and ...
The bird has never gotten much credit for being intelligent. But the reinforcement learning powering the world’s most advanced AI systems is far more pigeon than human. In 1943, while the world’s ...
1 School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA. 2 Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA. As cloud ...
This repo contains the repeatability package of the paper "Training Verifiably Robust Agnets Using Set-Based Reinforcement Learning", Wendl et. al, 2024.
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