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

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 …

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 …

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

Evolutionary Reinforcement Learning (ERL), which integrates Evolutionary Algorithms (EAs)
and Reinforcement Learning (RL) for optimization, has demonstrated remarkable …

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 …

Real-time measurement parameters are crucial for diagnosing faults in aero-engine gas
path performance, ensuring engine reliability, and mitigating potential economic losses …

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 …