Abstract: Inverse reinforcement learning optimal control is under the framework of learner–expert, the learner system can learn expert system's trajectory and optimal control policy via a ...
The Fraunhofer Institute for Photonic Microsystems (IPMS) has announced Q-Dice, a high-performance Quantum Random Number ...
Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
Deep reinforcement learning (DRL) algorithms have been widely applied in user cold-start recommender systems because they can gradually capture users’ dynamic interest preferences. Deep Q-Networks ...
Artificial Intelligence (AI) has undergone remarkable progress over the past few decades, and one of the most transformative areas within this field is Reinforcement Learning (RL). Unlike supervised ...
ABSTRACT: Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle ...
Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...
This important study uses reinforcement learning to study how turbulent odor stimuli should be processed to yield successful navigation. The authors find that there is an optimal memory length over ...
But the real question is: connected to what? Parker Woodroof, Ph.D., a social media expert and associate professor of marketing at the Collat School of Business at the University of Alabama at ...
Reinforcement Learning (RL) is no longer just a research curiosity—it’s the engine behind game-changing advances in robotics, autonomous systems, and intelligent control. But with so many algorithms ...
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