A new ensemble machine learning-based prediction mechanism reinitializes evolutionary algorithm populations after ...

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

A simulation study in Cluster Computing reports that a hybrid chaotic fire hawk and pufferfish optimization algorithm lowered ...

This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, ...

Human social learning is increasingly occurring on online social platforms, such as Twitter, Facebook, and TikTok. On these platforms, algorithms exploit existing social-learning biases (i.e., towards ...

A backpropagation algorithm, or backward propagation of errors, is an algorithm that's used to help train neural network models. The algorithm adjusts the network's weights to minimize any gaps -- ...

Supervised learning algorithms learn from labeled data, where the desired output is known. These algorithms aim to build a model that can predict the output for new, unseen input data. Let’s take a ...