4 citations · 4 across the 6 of their papers we have counts for
6 papers
Generative Embodied Multiple Behavior Control Systems for Human-like Agents
Chongyu Bao, Haokai Yang, Yuhan Wang +3
Building autonomous agents that reproduce human behavior in realistic 3D environments has been a longstanding objective in AI. Cognitive neuroscience commonly believes that human b…
Semantic Communications for Vehicle-Based Mission-Critical Services: Challenges and Solutions
Hui Zhou, Jiaying Guo, Marios Aristodemou +5
As mission-critical (MC) services such as Unmanned Aerial Vehicles (UAVs) based emergency communication and Internet of Vehicles (IoVs) enabled autonomous driving emerge, the tradi…
Galaxy: A Cognition-Centered Framework for Proactive, Privacy-Preserving, and Self-Evolving LLM Agents
Chongyu Bao, Ruimin Dai, Yangbo Shen +4
Intelligent personal assistants (IPAs) such as Siri and Google Assistant are designed to enhance human capabilities and perform tasks on behalf of users. The emergence of LLM agent…
A mini-batch training strategy for deep subspace clustering networks
Yuxuan Jiang, Chenwei Yu, Zhi Lin +1
Mini-batch training is a cornerstone of modern deep learning, offering computational efficiency and scalability for training complex architectures. However, existing deep subspace…
Fully Independent Communication in Multi-Agent Reinforcement Learning
Rafael Pina, Varuna De Silva, Corentin Artaud +1
Multi-Agent Reinforcement Learning (MARL) comprises a broad area of research within the field of multi-agent systems. Several recent works have focused specifically on the study of…
Staged Reinforcement Learning for Complex Tasks through Decomposed Environments
Rafael Pina, Corentin Artaud, Xiaolan Liu +1
Reinforcement Learning (RL) is an area of growing interest in the field of artificial intelligence due to its many notable applications in diverse fields. Particularly within the c…