Abstract: Offline reinforcement learning (RL) has been widely used in practice due to its efficient data utilization, but it still faces the challenge of training vulnerability caused by policy ...

Abstract: In this article, we introduce a novel framework that combines constraint logic programming (CLP) with deep reinforcement learning (DRL) to create adaptive environments for continual learning ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...