This research aims to explore the potential applications of artificial intelligence (AI) methods, such as reinforcement learning (RL) and artificial neural networks (ANN), in controlling inverter ...

We present BiRLNN, a bidirectional molecular design framework that combines recurrent neural networks with reinforcement learning to optimize drug-like properties of generated compounds. We examined ...

Nearly a century ago, psychologist B.F. Skinner pioneered a controversial school of thought, behaviorism, to explain human and animal behavior. Behaviorism directly inspired modern reinforcement ...

As cities continue to expand, railways are expected to become an important component of urban mobility systems. Compared with ...

Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain a mathematical function, similar to neurons that each have ...

ChatGPT and other AI tools are upending our digital lives, but our AI interactions are about to get physical. Humanoid robots trained with a particular type of AI to sense and react to their world ...

Engineers have uncovered an unexpected pattern in how neural networks -- the systems leading today's AI revolution -- learn, suggesting an answer to one of the most important unanswered questions in ...

From image captioning and neural networks to Tesla Autopilot and OpenAI, Andrej Karpathy has helped shape modern AI research. Here are seven major breakthroughs and contributions that influenced ...

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...