FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to Computational Intelligence for applied research. The contributions to the ninth in the series of FLINS conferences cover state-of-the-art research, development, and technology for computational intelligence systems — both from foundations and applications points-of-view.

This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas. The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.

Information modeling and knowledge bases are important technologies for academic and industrial research that goes beyond the traditional borders of information systems and computer science. The amount and complexity of information to be dealt with grows continually, as do the levels of abstraction and the size of databases. This book presents the proceedings of the 30th International Conference on Information Modelling and Knowledge Bases (EJC2020), due to be held in Hamburg, Germany on 8 and 9 June 2020, but instead held as a virtual conference on the same dates due to the Corona-virus pandemic restrictions. The conference provides a research forum for the exchange of scientific results and experiences, and brings together experts from different areas of computer science and other disciplines with a common interest in information modeling and knowledge bases. The subject touches on many disciplines, with philosophy and logic, cognitive science, knowledge management, linguistics and management science, as well as the emerging fields of data science and machine learning, all being relevant areas. The 23 reviewed, selected, and upgraded contributions included here are the result of presentations, comments, and discussions from the conference, and reflect the themes of the conference sessions: learning and linguistics; systems and processes; data and knowledge representation; models and interfaces; formalizations and reasoning; models and modeling; machine learning; models and programming; environment and predictions; modeling emotion; and social networks. The book provides an overview of current research and applications, and will be of interest to all those working in the field.

This double volume LNAI 13925-13926 constitutes the thoroughly refereed proceedings of the 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, held in Shanghai, China, in July 2023. The 50 full papers and 20 short papers presented were carefully reviewed and selected from 129 submissions. The IEA/AIE 2023 conference on applications of applied intelligent systems to solve real-life problems in all areas including business and finance, science, engineering, industry, cyberspace, bioinformatics, automation, robotics, medicine and biomedicine, and human-machine interactions.

Machine learning algorithms allow computers to learn without being explicitly programmed. Their application is now spreading to highly sophisticated tasks across multiple domains, such as medical diagnostics or fully autonomous vehicles. While this development holds great potential, it also raises new safety concerns, as machine learning has many specificities that make its behaviour prediction and assessment very different from that for explicitly programmed software systems. This book addresses the main safety concerns with regard to machine learning, including its susceptibility to environmental noise and adversarial attacks. Such vulnerabilities have become a major roadblock to the deployment of machine learning in safety-critical applications. The book presents up-to-date techniques for adversarial attacks, which are used to assess the vulnerabilities of machine learning models; formal verification, which is used to determine if a trained machine learning model is free of vulnerabilities; and adversarial training, which is used to enhance the training process and reduce vulnerabilities. The book aims to improve readers’ awareness of the potential safety issues regarding machine learning models. In addition, it includes up-to-date techniques for dealing with these issues, equipping readers with not only technical knowledge but also hands-on practical skills.

Artificial Intelligence (AI) is being widely recognized to be the power that will fuel the future global digital economy. AI in the past few years has gained geostrategic importance and a large number of countries are striving hard to stay ahead with their policy initiatives to get their country already. AI is a continually advancing and expanding field and AI readiness will lead to better opportunities and increased levels of understanding. It will help them visualize jobs of the future and prepare for them. Its multidisciplinary nature will help to make connections between all other subjects thereby adding value and giving a different perspective for all. The CBSE curriculum focuses on building AI readiness in young minds. The importance of skill-based education and the value of project-related work is clear in order to "effectively harness the potential of AI in a sustainable manner to make India's next-generation 'AI ready'. AB a beginning in this direction, CBSE introduced Artificial Intelligence starting from Class VI onward. Students should opt for this curriculum to become future-ready and become at par with their counterparts at a global level. The aim is to strive together to make our students future-ready and help they work on incorporating Artificial Intelligence to improve their learning experience. Goyal Brothers Prakashan

The International Symposium on Distributed Computing and Artificial Intel- gence (DCAI ́10) is an annual forum that brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application to provide efficient solutions to real problems. This symposium is organized by the Biomedicine, Intelligent System and Edu- tional Technology Research Group (http://bisite. usal. es/) of the University of - lamanca. The present edition has been held at the Polytechnic University of - lencia, from 7 to 10 September 2010, within the Congreso Español de Informática (CEDI 2010). Technology transfer in this field is still a challenge, with a large gap between academic research and industrial products. This edition of DCAI aims at contributing to reduce this gap, with a stimulating and productive forum where these communities can work towards future cooperation with social and econo- cal benefits. This conference is the forum in which to present application of in- vative techniques to complex problems. Artificial intelligence is changing our - ciety. Its application in distributed environments, such as internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to cite some, is continuously increasing, becoming an e- ment of high added value with social and economic potential, both industry, life quality and research. These technologies are changing constantly as a result of the large research and technical effort being undertaken in universities, companies.

This book presents computational intelligence methodologies and its applications to sustainable development goals. Along 18 chapters prepared by reputed scientists around the world, this book explores and focuses on the impacts produced by the application of artificial intelligence and mainly of computational intelligence, in sustainable development goals and on analysing how particularly computational intelligence can influence the ability to comply in a timely manner with all the sustainable development goals. Specialists from STEM areas will find in this book an attractive showcase of instances and research lines to be explored.

There has been a movement over the years to make machines intelligent. With the advent of modern technology, AI has become the core part of day-to-day life. But it is accentuated to have a book that keeps abreast of all the state-of-the-art concepts (pertaining to AI) in simplified, explicit and elegant way, expounding on ample examples so that the beginners are able to comprehend the subject with ease. The book on Artificial Intelligence, dexterously divided into 21 chapters, fully satisfies all these pressing needs. It is intended to put each and every concept related to intelligent system in front of the readers in the most simplified way so that while understanding the basic concepts, they will develop thought process that can contribute to the building of advanced intelligent systems. Various cardinal landmarks pertaining to the subject such as problem solving, search techniques, intelligent agents, constraint satisfaction problems, knowledge representation, planning, machine learning, natural language processing, pattern recognition, game playing, hybrid and fuzzy systems, neural network-based learning and future work and trends in AI are now under the single umbrella of this book, thereby showing a nice blend of theoretical and practical aspects. With all the latest information incorporated and several pedagogical attributes included, this textbook is an invaluable learning tool for the undergraduate and postgraduate students of computer science and engineering, and information technology. KEY FEATURES • Highlights a clear and concise presentation through adequate study material • Follows a systematic approach to explicate fundamentals as well as recent advances in the area • Presents ample relevant problems in the form of multiple choice questions, concept review questions, critical thinking exercise and project work • Incorporates various case studies for major topics as well as numerous industrial examples