Cooperative Output Regulation of Heterogeneous Directed Multi-Agent Systems: A Fully Distributed Model-Free Reinforcement Learning Framework

Research on Cooperative Output Regulation of Heterogeneous Directed Multi-Agent Systems: A Fully Distributed Model-Free Reinforcement Learning Framework Background In recent years, the study of distributed control and optimization has demonstrated broad application prospects in smart transportation, smart grids, distributed energy systems, and othe...

A Practical Distributed Randomness Beacon with Optimal Amortized Communication Complexity

Cutting-edge Breakthrough in Distributed Randomness Beacon (DRB) Research — A Practical Solution Optimizing Communication Complexity for Large-scale Applications In numerous technological fields today, a reliable randomness beacon is a critical tool, playing a vital role in the security of cryptography, blockchain, electronic voting, and many other...

Observer-Based Event-Triggered Formation Tracking Control for Second-Order Multi-Agent Systems in Constrained Region

Review of Research on Time-Varying Formation Tracking Control for Multi-Agent Systems in Constrained Regions Multi-Agent Systems (MAS) have drawn significant attention in recent years due to their broad applications in fields such as multiple autonomous underwater vehicles (AUVs) and multi-rotor drones. Additionally, MAS present potential benefits ...

New Results on Finite-Time Stability and Instability Theorems for Stochastic Nonlinear Time-Varying Systems

New Results on Finite-Time Stability and Instability Theorems for Stochastic Nonlinear Time-Varying Systems 1. Research Background and Significance Stability theory is a central topic in systems theory and engineering applications, serving as the fundamental consideration in system analysis and synthesis. In stability theory, the two most commonly ...

An End-to-End Visual Semantic Localization Network Using Multi-View Images

A Study on End-to-End Visual Semantic Localization Using Multi-View Images Background and Research Significance With the rapid development of intelligent driving technology, precise localization of autonomous vehicles has become a hot topic in research and industry. Accurate vehicle localization is not only a core module of autonomous driving but a...

Satellite-Assisted 6G Wide-Area Edge Intelligence: Dynamics-Aware Task Offloading and Resource Allocation for Remote IoT Services

Satellite-Assisted 6G Wide-Area Edge Intelligence: Dynamics-Aware Task Offloading and Resource Allocation for Remote IoT Services

Satellite-Assisted 6G Wide-Area Edge Intelligence: Dynamics-Aware Task Offloading and Resource Allocation for Remote IoT Services Background Introduction With the advent of the 6G mobile communication network, the traditional Internet of Things (IoT) architecture is gradually transforming into the new paradigm of the intelligent Internet of Everyth...

E-Predictor: An Approach for Early Prediction of Pull Request Acceptance

Research Breakthrough on Early Prediction of Pull Request Acceptance In recent years, open-source software (OSS) development has gradually become one of the mainstream software development models, heavily relying on collaboration among developers. The Pull Request (PR) mechanism, widely applied in distributed software development, improves collabor...

Characterizing the App Recommendation Relationships in the iOS App Store: A Complex Network’s Perspective

Analyzing the Complex Network of iOS App Store Recommendation Relationships Background Mobile applications (referred to as mobile apps) are a vital part of the modern Internet ecosystem. However, with the exponential growth in the number of mobile apps, it has become increasingly difficult for users to find desired apps in app stores and for develo...

Federated Local Causal Structure Learning Algorithm

Intersection of Data Privacy and Causal Learning: Breakthrough in Federated Local Causal Structure Learning With the rapid development of big data and artificial intelligence, analyzing and inferring causal relationships while ensuring data privacy in sensitive fields such as healthcare and finance has become a key challenge for academia and indust...

Towards Few-Shot Mixed-Type Dialogue Generation

A Breakthrough in Mixed-Type Dialogue Generation: Few-Shot Learning Research One of the significant goals of Artificial Intelligence (AI) is to build agents capable of conducting multiple types of natural language dialogues. The industry and academia have long awaited the creation of dialogue models that can handle both open-domain dialogues and ta...