Explainable Artificial Intelligence for Autonomous Vehicles: Concepts, Challenges, and Applications, Malik, Kamal ; Sharma, Moolchand ; Deswal, Suman ;
Автор: Calvaresi Davide, Najjar Amro, Winikoff Michael Название: Explainable, Transparent Autonomous Agents and Multi-Agent Systems: Second International Workshop, Extraamas 2020, Auckland, New Zealand, May 9-13, 20 ISBN: 3030519236 ISBN-13(EAN): 9783030519230 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the proceedings of the Second International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, EXTRAAMAS 2020, which was due to be held in Auckland, New Zealand, in May 2020.
Автор: Mar Marcos; Jose M. Juarez; Richard Lenz; Grzegorz Название: Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems ISBN: 3030374459 ISBN-13(EAN): 9783030374457 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes revised selected papers from the AIME 2019 workshops KR4HC/ProHealth 2019, the Workshop on Knowledge Representation for Health Care and Process-Oriented Information Systems in Health Care, and TEAAM 2019, the Workshop on Transparent, Explainable and Affective AI in Medical Systems.
Автор: Rutkowski Tom Название: Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance ISBN: 3030755207 ISBN-13(EAN): 9783030755201 Издательство: Springer Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainable. However, in many applications, e.g., medical diagnosis or venture capital investment recommendations, it is essential to explain the rationale behind AI systems decisions or recommendations.
Автор: Davide Calvaresi; Amro Najjar; Michael Schumacher; Название: Explainable, Transparent Autonomous Agents and Multi-Agent Systems ISBN: 303030390X ISBN-13(EAN): 9783030303907 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the proceedings of the First International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, EXTRAAMAS 2019, held in Montreal, Canada, in May 2019. The 12 revised and extended papers presented were carefully selected from 23 submissions. explainable agent simulations;
Автор: Wojciech Samek; Gr?goire Montavon; Andrea Vedaldi; Название: Explainable AI: Interpreting, Explaining and Visualizing Deep Learning ISBN: 3030289532 ISBN-13(EAN): 9783030289539 Издательство: Springer Рейтинг: Цена: 68930.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner.The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Название: Explainable artificial intelligence for smart cities ISBN: 1032001127 ISBN-13(EAN): 9781032001128 Издательство: Taylor&Francis Рейтинг: Цена: 102070.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. This book provides a timely, global reference source about cutting edge research efforts to ensure the XAI factor in smart city-oriented developments.
Автор: Markus Kr?tzsch; Daria Stepanova Название: Reasoning Web. Explainable Artificial Intelligence ISBN: 3030314227 ISBN-13(EAN): 9783030314224 Издательство: Springer Рейтинг: Цена: 54030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume contains lecture notes of the 15th Reasoning Web Summer School (RW 2019), held in Bolzano, Italy, in September 2019. The research areas of Semantic Web, Linked Data, and Knowledge Graphs have recently received a lot of attention in academia and industry. Since its inception in 2001, the Semantic Web has aimed at enriching the existing Web with meta-data and processing methods, so as to provide Web-based systems with intelligent capabilities such as context awareness and decision support. The Semantic Web vision has been driving many community efforts which have invested a lot of resources in developing vocabularies and ontologies for annotating their resources semantically. Besides ontologies, rules have long been a central part of the Semantic Web framework and are available as one of its fundamental representation tools, with logic serving as a unifying foundation. Linked Data is a related research area which studies how one can make RDF data available on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shown useful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains.
Автор: Kamath Uday, Liu John Название: Explainable Artificial Intelligence: An Introduction to Xai ISBN: 3030833550 ISBN-13(EAN): 9783030833558 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 1. Introduction to Interpretability and Explainability.- 2. Pre-Model Interpretability and Explainability.- 3. Model Visualization Techniques and Traditional Interpretable Algorithms.- 4. Model Interpretability: Advances in Interpretable Machine Learning.- 5. Post-hoc Interpretability and Explanations.- 6. Explainable Deep Learning.- 7. Explainability in Time Series Forecasting, Natural Language Processing, and Computer Vision.- 8. XAI: Challenges and Future.
Автор: Holzinger Andreas, Goebel Randy, Fong Ruth Название: xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Paper ISBN: 3031040821 ISBN-13(EAN): 9783031040825 Издательство: Springer Рейтинг: Цена: 37260.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans. Explainable AI is receiving huge interest in the machine learning and AI research communities, across academia, industry, and government, and there is now an excellent opportunity to push towards successful explainable AI applications. This volume will help the research community to accelerate this process, to promote a more systematic use of explainable AI to improve models in diverse applications, and ultimately to better understand how current explainable AI methods need to be improved and what kind of theory of explainable AI is needed. After overviews of current methods and challenges, the editors include chapters that describe new developments in explainable AI. The contributions are from leading researchers in the field, drawn from both academia and industry, and many of the chapters take a clear interdisciplinary approach to problem-solving. The concepts discussed include explainability, causability, and AI interfaces with humans, and the applications include image processing, natural language, law, fairness, and climate science.
Автор: Rutkowski Название: Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance ISBN: 3030755231 ISBN-13(EAN): 9783030755232 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainable. However, in many applications, e.g., medical diagnosis or venture capital investment recommendations, it is essential to explain the rationale behind AI systems decisions or recommendations.
Автор: Gaur Название: Explainable Artificial Intelligence for Intelligent Transportation Systems ISBN: 3031096436 ISBN-13(EAN): 9783031096433 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Transportation typically entails crucial “life-death” choices, delegating crucial decisions to an AI algorithm without any explanation poses a serious threat. Hence, explainability and responsible AI is crucial in the context of intelligent transportation. In Intelligence Transportation System (ITS) implementations such as traffic management systems and autonomous driving applications, AI-based control mechanisms are gaining prominence. Explainable artificial intelligence for intelligent transportation system tackling certain challenges in the field of autonomous vehicle, traffic management system, data integration and analytics and monitor the surrounding environment. The book discusses and inform researchers on explainable Intelligent Transportation system. It also discusses prospective methods and techniques for enabling the interpretability of transportation systems. The book further focuses on ethical considerations apart from technical considerations.
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