Focuses on developing neural-symbolic deep neural network (DNN) architectures. The aim is to integrate symbolic reasoning with neural networks for AGI, demonstrating use for experiential learning or higher-order reasoning. Investigates how embedding logic rules can improve reasoning capabilities of graph neural networks, LLMs, and other deep learning models.