Search Results for author:
Found 11 papers, 3 papers with code
Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities
For that, this paper aims to provide a comprehensive survey on applications, challenges, and opportunities of GAI in unmanned vehicle swarms.
Apollo's Oracle: Retrieval-Augmented Reasoning in Multi-Agent Debates
Addressing the challenge of cognitive constraints, we introduce a novel framework, the Multi-Agent Debate with Retrieval Augmented (MADRA).
Adapting Segment Anything Model for Change Detection in HR Remote Sensing Images
In this work, we aim to utilize the strong visual recognition capabilities of VFMs to improve the change detection of high-resolution Remote Sensing Images (RSIs).
Leveraging Optical Communication Fiber and AI for Distributed Water Pipe Leak Detection
Detecting leaks in water networks is a costly challenge.
Hierarchical Catalogue Generation for Literature Review: A Benchmark
Scientific literature review generation aims to extract and organize important information from an abundant collection of reference papers and produces corresponding reviews while lacking a clear and logical hierarchy.
Compressed domain vibration detection and classification for distributed acoustic sensing
Distributed acoustic sensing (DAS) is a novel enabling technology that can turn existing fibre optic networks to distributed acoustic sensors.
Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspective
In this paper, we provide a comprehensive review for the economic and game theoretic approaches proposed in the literature to design various schemes for stimulating data owners to participate in FL training process.
Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey
Then, we review a number of applications of MARL to solve emerging issues in future Internet.
Co-Imitation Learning without Expert Demonstration
Imitation learning is a primary approach to improve the efficiency of reinforcement learning by exploiting the expert demonstrations.
Dynamic Network Service Selection in Intelligent Reflecting Surface-Enabled Wireless Systems: Game Theory Approaches
To formulate the SP and network service selection, we adopt an evolutionary game in which the users are able to adapt their network selections depending on the utilities that they achieve.
Computer Science and Game Theory
Data-Driven Machine Learning Techniques for Self-healing in Cellular Wireless Networks: Challenges and Solutions
As an important component in SON, self-healing is defined as a network paradigm where the faults of target networks are mitigated or recovered by automatically triggering a series of actions such as detection, diagnosis and compensation.
