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Multi-Agent Reinforcement Learning based Edge Content Caching for Connected Autonomous Vehicles in IoV

ACM Transactions on Autonomous and Adaptive systems 1000年

作者： Xiaolong Xu Linjie Gu Muhammad Bilal Maqbool Khan Yiping Wen Guoqiang Liu Yuan Yuan School of Software Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services Nanjing University of Information Science and Technology China Changwang School of Honors Nanjing University of Information Science and Technology China Department of Computer and Electronics Systems Engineering Hankuk University of Foreign Studies Korea Department of IT and Computer Science Pak-Austria Fachhochschule-Institute of Applied Sciences and Technology Pakistan School of Computer Science and Engineering Hunan University of Science and Technology China School of Software Nanjing University of Information Science and Technology China School of Computer Science and Engineering Beihang University State Key Laboratory of Software Development Environment Zhongguancun Laboratory China

Connected Autonomous Vehicle (CAV) Driving, as a data-driven intelligent driving technology within the Internet of Vehicles (IoV), presents significant challenges to the efficiency and security of real-time data management. The combination of Web3.0 and edge content caching holds promise in providing low-latency data access for CAVs’ real-time applications. Web3.0 enables the reliable pre-migration of frequently requested content from content providers to edge nodes. However, identifying optimal edge node peers for joint content caching and replacement remains challenging due to the dynamic nature of traffic flow in IoV. Addressing these challenges, this article introduces GAMA-Cache, an innovative edge content caching methodology leveraging Graph Attention Networks (GAT) and Multi-Agent Reinforcement Learning (MARL). GAMA-Cache conceptualizes the cooperative edge content caching issue as a constrained Markov decision process. It employs a MARL technique predicated on cooperation effectiveness to discern optimal caching decisions, with GAT augmenting information extracted from adjacent nodes. A distinct collaborator selection mechanism is also developed to streamline communication between agents, filtering out those with minimal correlations in the vector input to the policy network. Experimental results demonstrate that, in terms of service latency and delivery failure, the GAMA-Cache outperforms other state-of-the-art MARL solutions for edge content caching in IoV.

关键词： Content Caching Reinforcement Learning Connected Autonomous Driving

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An X Language-Driven Framework for Systematic Development of Digital Twin Healthcare systems

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ACM Transactions on Multimedia Computing, Communications, and Applications 1000年

作者： Kunyu Xie Lin Zhang Yuan Yang Xiaohe Li Ridha Khedri Zhen Chen M. Jamal Deen Simulation Technology Innovation Center Hangzhou International Innovation Institute of Beihang University Hangzhou 311115 Zhejiang China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China State Key Laboratory of Intelligent Manufacturing Systems Technology Beijing 100191 China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China Shenzhen Third People’s Hospital & Second Hospital Affiliated to Southern University of Science and Technology Shenzhen 518112 Guangdong China Dept. of Computing and Software McMaster University Hamilton Ontario Canada L8S 4K1 Department of Electrical and Computer Engineering McMaster University Hamilton ON L8S 4L8 Canada

The rapid advancements in big data and the Internet of Things (IoT) have significantly accelerated the digital transformation of medical institutions, leading to the widespread adoption of Digital Twin Healthcare (DTH). The Cloud DTH Platform (CDTH) serves as a cloud-based framework that integrates DTH models, healthcare resources, patient data, and medical services. By leveraging real-time data from medical devices, the CDTH platform enables intelligent healthcare services such as disease prediction and medical resource optimization. However, the platform functions as a system of systems (SoS), comprising interconnected yet independent healthcare services. This complexity is further compounded by the integration of both black-box AI models and domain-specific mechanistic models, which pose challenges in ensuring the interpretability and trustworthiness of DTH models. To address these challenges, we propose a Model-Based systems engineering (MBSE)-driven DTH modeling methodology derived from systematic requirement and functional analyses. To implement this methodology effectively, we introduce a DTH model development approach using the X language, along with a comprehensive toolchain designed to streamline the development process. Together, this methodology and toolchain form a robust framework that enables engineers to efficiently develop interpretable and trustworthy DTH models for the CDTH platform. By integrating domain-specific mechanistic models with AI algorithms, the framework enhances model transparency and reliability. Finally, we validate our approach through a case study involving elderly patient care, demonstrating its effectiveness in supporting the development of DTH models that meet healthcare and interpretability requirements.

关键词： Digital Twin Model-based system engineering X Language Medical Cyber-Physical systems Digital Twin Healthcare Design

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intelligent Agents and Their Applications 1

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丛书名： Studies in Fuzziness and Soft Computing

1000年

作者： Lakhmi C. Jain Nikhil Ichalkaranje Zhengxin Chen

ISBN: (数字)9783790817867

ISBN: (纸本)9783790814699;9783790825107

intelligent agents are one of the most promising business tools in our information rich world. An intelligent agent consists of a software system capable of performing intelligent tasks within a dynamic and unpredictable environment. They can be characterised by various attributes including: autonomous, adaptive, collaborative, communicative, mobile, and reactive. Many problems are not well defined and the information needed to make decisions is not available. These problems are not easy to solve using conventional computing approaches. Here, the intelligent agent paradigm may play a major role in helping to solve these problems. This book, written for application researchers, covers a broad selection of research results that demonstrate, in an authoritative and clear manner, the applications of agents within our information society.

关键词： Artificial Intelligence computer-Aided engineering (CAD, CAE) and Design Electrical engineering

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Agent and Multi-Agent systems: Technologies and Applications 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Anne Håkansson Ngoc Thanh Nguyen Ronald L. Hartung Robert J. Howlett Lakhmi C. Jain

ISBN: (数字)9783642016653

ISBN: (纸本)9783642016646

This volume contains the proceedings of the Third KES Symposium on Agent and Multi-agent systems – Technologies and Applications (KES-AMSTA 2009)––held at Uppsala University in Sweden during June 3-5, 2009. The symposium was organized by Uppsala University, KES International and its Focus Group on Agent and Multi-agent systems. The KES-AMSTA Symposium series is a sub-series of the KES Conference series. Following the successes of the First KES Symposium on Agent and Multi-agent systems – Technologies and Applications (KES-AMSTA 2007), held in Wroclaw, Poland, from May 31 to 1 June 2007––and the Second KES Symposium on Agent and Multi-agent systems – Technologies and Applications (KES-AMSTA 2008) held in Incheon, Korea, March 26-28, 2008––KES-AMSTA 2009 featured keynote talks, oral and poster presentations, and a number of workshops and invited sessions, closely aligned to the themes of the conference. The aim of the symposium was to provide an international forum for scientific - search into the technologies and applications of agent and multi-agent systems. Agent and multi-agent systems are an innovative type of modern software system and have long been recognized as a promising technology for constructing autonomous, c- plex and intelligent systems. A key development in the field of agent and multi-agent systems has been the specification of agent communication languages and formali- tion of ontologies. Agent communication languages are intended to provide standard declarative mechanisms for agents to communicate knowledge and make requests of each other, whereas ontologies are intended for conceptualization of the knowledge domain.

关键词： Artificial Intelligence Data Mining and Knowledge Discovery Database Management computers and Society Information systems Applications (incl. Internet) computer Appl. in Administrative Data Processing

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SOFSEM 2012: Theory and Practice of computer Science 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Mária Bieliková Gerhard Friedrich Georg Gottlob Stefan Katzenbeisser György Turán

ISBN: (数字)9783642276606

ISBN: (纸本)9783642276590

This book constitutes the refereed proceedings of the 38th Conference on Current Trends in Theory and Practice of computer Science, SOFSEM 2012, held in Špindlerův Mlýn, Czech Republic, in January 2012. The 43 revised papers presented in this volume were carefully reviewed and selected from 121 submissions. The book also contains 11 invited talks, 10 of which are in full-paper length. The contributions are organized in topical sections named: foundations of computer science; software and Web engineering; cryptography, security, and verification; and artificial intelligence.

关键词： Algorithm Analysis and Problem Complexity Software engineering Data Storage Representation Discrete Mathematics in computer Science computer Communication Networks Database Management

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Recent Trends in Applied Artificial Intelligence 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Moonis Ali Tibor Bosse Jan Treur Koen V. Hindriks Catholijn M. Jonker Mark Hoogendoorn

ISBN: (数字)9783642385773

ISBN: (纸本)9783642385766

This volume constitutes the thoroughly refereed conference proceedings of the 26th International Conference on Industrial engineering and Other Applications of Applied Intelligence systems, IEA/AIE 2013, held in Amsterdam, The Netherlands, in June 2013. The total of 71 papers selected for the proceedings were carefully reviewed and selected from 185 submissions. The papers focus on the following topics: auctions and negotiation, cognitive modeling, crowd behavior modeling, distributed systems and networks, evolutionary algorithms, knowledge representation and reasoning, pattern recognition, planning, problem solving, robotics, text mining, advances in recommender systems, business process intelligence, decision support for safety-related systems, innovations in intelligent computation and applications, intelligent image and signal processing, and machine learning methods applied to manufacturing processes and production systems.

关键词： Artificial Intelligence Information systems Applications (incl. Internet) Algorithm Analysis and Problem Complexity Data Mining and Knowledge Discovery computer Imaging, Vision, Pattern Recognition and Graphics computer Science, general

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Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing

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ACM Computing Surveys 1000年

作者： Md Mehedi Hasan Moloud Abdar Abbas Khosravi Uwe Aickelin Pietro Lio Ibrahim Hossain Ashikur Rahman Saeid Nahavandi Institute for Intelligent Systems Research and Innovation Deakin University Geelong Australia Institute for Intelligent Systems Research and Innovation Deakin University Burwood Australia School of Computing and Information Systems The University of Melbourne Melbourne Australia Department of Computer Science and Technology Cambridge University Cambridge United Kingdom of Great Britain and Northern Ireland Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Swinburne University of Technology Melbourne Australia

Although neural networks (especially deep neural networks) have achieved better-than-human performance in many fields, their real-world deployment is still questionable due to the lack of awareness about the limitations in their knowledge. To incorporate such awareness in the machine learning model, prediction with reject option (also known as selective classification or classification with abstention) has been proposed in the literature. In this paper, we present a systematic review of the prediction with the reject option in the context of various neural networks. To the best of our knowledge, this is the first study focusing on this aspect of neural networks. Moreover, we discuss different novel loss functions related to the reject option and post-training processing (if any) of network output for generating suitable measurements for knowledge awareness of the model. Finally, we address the application of the rejection option in reducing the prediction time for real-time problems and present a comprehensive summary of the techniques related to the reject option in the context of a wide variety of neural networks. Our code is available on GitHub: https://***/MehediHasanTutul/Reject_option.

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Noninvasive Brain–Machine Interfaces for Robotic Devices

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Control, Robotics, and Autonomous systems 1000年第1期4卷 191-214页

作者： Luca Tonin José del R. Millán 1Intelligent Autonomous Systems Laboratory Department of Information Engineering Università degli Studi di Padova 35122 Padova Italy email: luca.tonin@dei.unipd.it 2Department of Electrical and Computer Engineering and Department of Neurology The University of Texas at Austin Austin Texas 78712 USA email: jose.millan@austin.utexas.edu

The last decade has seen a flowering of applications driven by brain–machine interfaces (BMIs), particularly brain-actuated robotic devices designed to restore the independence of people suffering from severe motor disabilities. This review provides an overview of the state of the art of noninvasive BMI-driven devices based on 86 studies published in the last 15 years, with an emphasis on the interactions among the user, the BMI system, and the robot. We found that BMIs are used mostly to drive devices for navigation (e.g., telepresence mobile robots), with BMI paradigms based mainly on exogenous stimulation, and the majority of brain-actuated robots adopt a discrete control strategy. Most critically, in only a few works have disabled people evaluated a brain-actuated robot. The review highlights the most urgent challenges in the field, from the integration between BMI and robotics to the need for a user-centered design to boost the translational impact of BMIs.

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intelligent Communication, Control and Devices 1

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丛书名： Advances in intelligent systems and Computing

1000年

作者： Sushabhan Choudhury R. Gowri Babu Sena Paul Dinh-Thuan Do

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Advances in Knowledge Discovery and Data Mining 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Joshua Zhexue Huang Longbing Cao Jaideep Srivastava

ISBN: (数字)9783642208478

ISBN: (纸本)9783642208461

The two-volume set LNAI 6634 and 6635 constitutes the refereed proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 revised full papers and 58 revised short papers were carefully reviewed and selected from 331 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, machine learning, artificial intelligence and pattern recognition, data warehousing and databases, statistics, knowledge engineering, behavior sciences, visualization, and emerging areas such as social network analysis.

关键词： Artificial Intelligence Information systems Applications (incl. Internet) Information Storage and Retrieval Database Management Algorithm Analysis and Problem Complexity computer Communication Networks

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