The vehicle routing problem with backhauls (VRPBs) is a challenging problem commonly
studied in computer science and operations research. Featured by linehaul (or delivery) and …

Transformer architectures have facilitated the development of large-scale and general-
purpose sequence models for prediction tasks in natural language processing and computer …

Greenhouses are key to ensuring food security and realizing a sustainable future for
agriculture. However, to ensure crop growth efficiency, greenhouses consume a significant …

Abstract The integration of Artificial Intelligence (AI) into supply chain management has
emerged as a pivotal avenue for enhancing efficiency and resilience in contemporary …

The Internet of Things (IoT) is undergoing significant advancements, driven by the
emergence of backscatter communication (BC) and artificial intelligence (AI). BC is an …

In value-based deep reinforcement learning with replay memories, the batch size parameter
specifies how many transitions to sample for each gradient update. Although critical to the …

The advent of machine learning (ML) and Artificial intelligence (AI) has brought about a
significant transformation across multiple industries, as it has facilitated the automation of …

In reinforcement learning, unsupervised skill discovery aims to learn diverse skills without
extrinsic rewards. Previous methods discover skills by maximizing the mutual information …

The traditional mode of Tunnel Boring Machine (TBM) operation is limited in their
applicability and efficiency to meet the growing demand for underground spaces. Current …

Multi-agent Reinforcement Learning (MARL) has gained wide attention in recent years and
has made progress in various fields. Specifically, cooperative MARL focuses on training a …