Explainable Ai For Communications And Networking
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Explainable AI for Communications and Networking
Explainable AI for Communications and Networking: Toward Responsible Automation gives a tour into the realm of Explainable Artificial Intelligence (XAI) and its impact on transparent and autonomous communication networks. The book equips readers from diverse backgrounds in communications and networking with a variety of XAI tools, metrics and frameworks to demystify AI systems through graphical taxonomies and mathematical formulations, which are further enriched with code snippets. The book also examines XAI implementation in wireless communications, network management, generative AI for telecom and cybersecurity, before presenting practical use-cases emanating from an industry perspective. Finally, the regulatory, ethical, and legal implications of XAI in telecommunications are reviewed, before concluding with key challenges and takeaways. - Includes XAI graphical taxonomies, metrics, formulations and code snippets. - Provides practical examples and use-cases from a telecom industry perspective. - Covers implementation guidelines (XAI libraries/implementation tools) tailored to a communications and networking context. - Highlights the application of XAI in wireless communications, network management, generative AI for telecom and cybersecurity. - Presents a thorough synthesis of the regulatory and ethical implications of XAI worldwide.
Artificial Intelligent Techniques for Wireless Communication and Networking
ARTIFICIAL INTELLIGENT TECHNIQUES FOR WIRELESS COMMUNICATION AND NETWORKING The 20 chapters address AI principles and techniques used in wireless communication and networking and outline their benefit, function, and future role in the field. Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts. The possibility of applying AI mechanisms towards security aspects in the communication domain is elaborated; also explored is the application side of integrated technologies that enhance AI-based innovations, insights, intelligent predictions, cost optimization, inventory management, identification processes, classification mechanisms, cooperative spectrum sensing techniques, ad-hoc network architecture, and protocol and simulation-based environments. Audience Researchers, industry IT engineers, and graduate students working on and implementing AI-based wireless sensor networks, 5G, IoT, deep learning, reinforcement learning, and robotics in WSN, and related technologies.
Explainable Artificial Intelligence
This three-volume set constitutes the refereed proceedings of the First World Conference on Explainable Artificial Intelligence, xAI 2023, held in Lisbon, Portugal, in July 2023. The 94 papers presented were thoroughly reviewed and selected from the 220 qualified submissions. They are organized in the following topical sections: Part I: Interdisciplinary perspectives, approaches and strategies for xAI; Model-agnostic explanations, methods and techniques for xAI, Causality and Explainable AI; Explainable AI in Finance, cybersecurity, health-care and biomedicine. Part II: Surveys, benchmarks, visual representations and applications for xAI; xAI for decision-making and human-AI collaboration, for Machine Learning on Graphs with Ontologies and Graph Neural Networks; Actionable eXplainable AI, Semantics and explainability, and Explanations for Advice-Giving Systems. Part III: xAI for time series and Natural Language Processing; Human-centered explanations and xAI for Trustworthy and Responsible AI; Explainable and Interpretable AI with Argumentation, Representational Learning and concept extraction for xAI.