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

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

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

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

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 …

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

The difficulty of appropriately assigning credit is particularly heightened in cooperative
MARL with sparse reward, due to the concurrent time and structural scales involved …

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 pathfinding (MAPF) is a problem that involves finding a set of non-conflicting
paths for a set of agents confined to a graph. In this work, we study a MAPF setting, where …

In reinforcement learning, the optimism in the face of uncertainty (OFU) is a mainstream
principle for directing exploration towards less explored areas, characterized by higher …