One of the most important functions of artificial intelligence, automated problem solving, consists mainly of the development of software systems designed to find solutions to problems. These systems utilize a search space and algorithms in order to reach a solution. Artificial Intelligence for Advanced Problem Solving Techniques offers scholars and practitioners cutting-edge research on algorithms and techniques such as search, domain independent heuristics, scheduling, constraint satisfaction, optimization, configuration, and planning, and highlights the relationship between the search categories and the various ways a specific application can be modeled and solved using advanced problem solving techniques.

Conventional computational methods, and even the latest soft computing paradigms, often fall short in their ability to offer solutions to many real-world problems due to uncertainty, imprecision, and circumstantial data. Hybrid intelligent computing is a paradigm that addresses these issues to a considerable extent. The Handbook of Research on Advanced Hybrid Intelligent Techniques and Applications highlights the latest research on various issues relating to the hybridization of artificial intelligence, practical applications, and best methods for implementation. Focusing on key interdisciplinary computational intelligence research dealing with soft computing techniques, pattern mining, data analysis, and computer vision, this book is relevant to the research needs of academics, IT specialists, and graduate-level students.

As modern technologies continue to develop and evolve, the ability of users to adapt with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies through artificial intelligence and computer simulation is necessary to fully realize the potential of tools in the 21st century. Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction provides emerging research in advanced trends in robotics, AI, simulation, and human-computer interaction. Readers will learn about the positive applications of artificial intelligence and human-computer interaction in various disciples such as business and medicine. This book is a valuable resource for IT professionals, researchers, computer scientists, and researchers invested in assistive technologies, artificial intelligence, robotics, and computer simulation.

Ongoing advancements in modern technology have led to significant developments in artificial intelligence. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Artificial Intelligence: Concepts, Methodologies, Tools, and Applications provides a comprehensive overview of the latest breakthroughs and recent progress in artificial intelligence. Highlighting relevant technologies, uses, and techniques across various industries and settings, this publication is a pivotal reference source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of artificial intelligence.

This book, Advanced Tools and Methods for Treewidth-Based Problem Solving, contains selected results from the author’s PhD studies, which were carried out from 2015 to 2021. For his PhD thesis, Markus Hecher received the EurAI Dissertation Award 2021 and the GI Dissertation Award 2021, amongst others. The aim of the book is to present a new toolkit for using the structural parameter of treewidth to solve problems in knowledge representation and reasoning (KR) and artificial intelligence (AI), thereby establishing both theoretical upper and lower bounds, as well as methods to deal with treewidth efficiently in practice. The key foundations outlined in the book provide runtime lower bounds – under reasonable assumptions in computational complexity – for evaluating quantified Boolean formulas and logic programs which match the known upper bounds already published in 2004 and 2009. The general nature of the developed tools and techniques means that a wide applicability beyond the selected problems and formalisms tackled in the book is anticipated, and it is hoped that the book will serve as a starting point for future theoretical and practical investigations, which will no doubt establish further results and gain deeper insights.

In 1991, Denis Hlynka and John Belland released Paradigms Regained, a well received reader for graduate students in the field of educational technology. The Role of Criticism in Understanding Problem Solving updates some of those ideas initially proposed in Paradigms Regained, and extends the conversation into the contemporary discourse regarding problem based learning (PBL). Paradigms proposed the idea of criticism as a third method for the conduction of educational research, the first two being qualitative and qualitative. The concept of criticism as a tool for research is not well established in educational technology, although it is well established in other educational research traditions such as Curriculum Studies. Unfortunately, it is not always clear how criticism can be applied. This book views criticism as a way to step back and look at an educational intervention within educational technology through a particular critical lens. Criticism is viewed as a valuable approach to guiding meta analyses and theoretical studies, serving to prevent the proverbial "spinning of the wheels" that often happens in educational research. By indicating new potential research questions and directions, criticism approaches can invigorate educational research. This book revisits the ideals of criticism in order to establish their usefulness for studying educational technology interventions to support problem based learning. First, a few foundational chapters set the stage for the conversations on criticism. Then, the role criticism can play in enhancing analysis and interpretation of the PBL literature is explored. Finally, case studies addressing the central concepts of the text are presented and dissected. This book represents a complete overhaul and rethinking of the use of criticism as a method for understanding and furthering the research area of PBL within the field of Educational technology.

The joint breakthrough of big data, cloud computing and deep learning has made artificial intelligence (AI) the new focus in the international arena. AI is a branch of computer science, developing intelligent machine with imitating, extending and augmenting human intelligence through artificial means and techniques to realize intelligent behaviour.This comprehensive compendium, consisting of 15 chapters, captures the updated achievements of AI. It is completely revised to reflect the current researches in the field, through numerous techniques and strategies to address the impending challenges facing computer scientists today.The unique volume is useful for senior or graduate students in the information field and related tertiary specialities. It is also a suitable reference text for professionals, researchers, and academics in AI, machine learning, electrical & electronic engineering and biocomputing.

Cyber security is a key focus in the modern world as more private information is stored and saved online. In order to ensure vital information is protected from various cyber threats, it is essential to develop a thorough understanding of technologies that can address cyber security challenges. Artificial intelligence has been recognized as an important technology that can be employed successfully in the cyber security sector. Due to this, further study on the potential uses of artificial intelligence is required. Methods, Implementation, and Application of Cyber Security Intelligence and Analytics discusses critical artificial intelligence technologies that are utilized in cyber security and considers various cyber security issues and their optimal solutions supported by artificial intelligence. Covering a range of topics such as malware, smart grid, data breachers, and machine learning, this major reference work is ideal for security analysts, cyber security specialists, data analysts, security professionals, computer scientists, government officials, researchers, scholars, academicians, practitioners, instructors, and students.

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers

Organized by: European Coordinating Committee for AI (ECCAI)