Three academic perspectives offer insights on the persistent misconceptions about artificial intelligence in healthcare.

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Abstract: To address the issues of slow convergence speed and poor path planning performance in dynamic obstacle environments. This paper proposes an improved Q-Learning path planning algorithm for ...

Abstract: This paper explores the application of Dyna-Q Learning algorithm in temperature process control especially in the chemical batch reactor. Since the precise control of temperature in batch is ...

The original version of this story appeared in Quanta Magazine. Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price.

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...

Lithology identification plays a pivotal role in logging interpretation during drilling operations, directly influencing drilling decisions and efficiency. Conventional lithology identification ...

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 ...

Every game of chess is a dialogue - A test of intention, creativity, and learning that echoes far beyond the board. “Chess Game” isn’t just another web-based chess app; it’s a bold experiment in ...