Augmented intelligence is an alternate approach of artificial intelligence (AI), which emphasizes AI’s assistive role. Augmented intelligence enhances human skills of reasoning in a robotic system or software by simulating expectancy, educational mining, problem solving, recollection, sequencing, and decision-making capabilities. It is based on a combination of techniques such as machine learning, deep learning and cognitive computing. This book explains artificial intelligence models that support assistive processes in different situations. The contributors aim to provide information to a diverse audience with groundbreaking developments in mathematical computing. The book presents 8 chapters on these topics: - Educational data mining in augmented reality virtual learning environment - Brain and computer interfaces - Tree-based tools for chemometric analysis of infrared spectra - Applications of deep learning in medical engineering - Bankruptcy prediction model using an enhanced boosting classifier - Reputation systems for mobile agent security - The crow search algorithm - COVID-19 diagnosis and treatment The contents attempt to integrate various facets of augmented Intelligence, by describing recent research developments and advanced topics of interest to academicians and researchers working on machine learning problems and AI.

This edited volume is based on contributions from the TCET-AECT “Human-Technology Frontier: Understanding the Learning of Now to Prepare for the Work of the Future Symposium” held in Denton, Texas on May 16-18, sponsored by AECT. The authors embrace an integrative approach to designing and implementing advances technologies in learning and instruction, and focus on the emerging themes of artificial intelligence, human-computer interactions, and the resulting instructional design. The volume will be divided into four parts: (1) Trends and future in learning and learning technologies expected in the next 10 years; (2) Technologies likely to have a significant impact on learning in the next 10 years; (3) Challenges that will need to be addressed and resolved in order to achieve significant and sustained improvement in learning; and (4) Reflections and insights from the Symposium that should be pursued and that can form the basis for productive research collaborations. The primary audience for this volume is academics and researchers in disciplines such as artificial intelligence, cognitive science, computer science, educational psychology, instructional design, human-computer interactions, information science, library science, and technology integration.

Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]

This volume constitutes the proceedings of the 18th International Conference on Intelligent Tutoring Systems, ITS 2022, held in Bucharest, Romania, in June 2022. The 14 full papers, 13 short papers and 11 poster papers presented in this volume were carefully reviewed and selected from 50 submissions. The papers are categorized into the following topical sub-headings: Tools and Methods for learning Sciences and Practices; Algorithms for Prediction, Recommendation and Classification in Learning Systems; Tutoring and Learning Systems: New Approaches, Framework and Theories.

This volume constitutes the proceedings of the 17th International Conference on Intelligent Tutoring Systems, ITS 2021, held in Athens, Greece, in June 2021. Due to COVID-19 pandemic the conference was held virtually. The 22 full papers, 22 short papers and 18 other papers presented in this volume were carefully reviewed and selected from 87 submissions. Conforming to the current move of education, work and leisure online, the title of ITS 2021 was “Intelligent Tutoring Systems in an online world”. Its objective was to present academic and research achievements of computer and cognitive sciences, artificial intelligence, and, due to its recent emergence, specifically, deep learning in tutoring and education

This book summarizes the research findings presented at the 3rd International Conference on Novel & Intelligent Digital Systems (NiDS 2023). NiDS 2023 held in Athens, Greece, during September 28–29, 2023, under the auspices of the Institute of Intelligent Systems. The conference was implemented hybrid, allowing participants to attend it either online or onsite. NiDS 2023 places significant importance on the innovations within intelligent systems and the collaborative research that empowers and enriches artificial intelligence (AI) in software development. It encourages high-quality research, establishing a forum for investigating the obstacles and cutting-edge breakthroughs in AI. The conference is designed for experts, researchers, and scholars in artificial and computational intelligence, as well as computer science in general, offering them the opportunity to delve into relevant, interconnected, and mutually complementary fields. By facilitating the exchange of ideas, the conference strengthens and broadens the network of researchers, academics, and industry representatives.

Artificial intelligence and intelligent digital systems have become indispensible to many areas of modern life. This book presents the proceedings of the 1st International Conference on Novelties in Intelligent Digital Systems (NIDS2021), held in Athens, Greece, from 30 September to 1 October 2021. The conference took place as a virtual event due to COVID-19 restrictions. The NIDS conference lays special emphasis on the novelties of intelligent systems and on the interdisciplinary research which enables, supports, and enhances Artificial Intelligence (AI) in software development. It promotes high-quality research, creating a forum for the exploration of challenges and new advances in AI, and addresses experts, researchers and scholars in the fields of artificial and computational intelligence in systems and in computer sciences in general, enabling them to learn more about pertinent, strongly related and mutually complementary fields. The conference promotes an exchange of ideas, reinforcing and expanding the network of researchers, academics, and market representatives. The 30 accepted papers included here have each been reviewed rigorously by two or three reviewers through a double-blind process which reflects the commitment of the IIS academic community to make NIDS a top-flight, selective and high-quality conference. They are grouped in 6 sections, and cover the topics of Learning; Extended Reality; Data Mining and Machine Learning; Health and Environment; Brain Assessment and Reasoning; and Computer Vision Describing some very significant research and reflecting many interesting new ideas, the book will be of interest to all those working in the field.