Exploring Artificial Intelligence: Survey Talks from the National Conference on Artificial Intelligence provides information pertinent to the distinct subareas of artificial intelligence research. This book discusses developments in machine learning techniques. Organized into six parts encompassing 16 chapters, this book begins with an overview of intelligent tutoring systems, which describes how to guide a student to learn new concepts. This text then links closely with one of the concerns of intelligent tutoring systems, namely how to interact through the utilization of natural language. Other chapters consider the various aspects of natural language understanding and survey the huge body of work that tries to characterize heuristic search programs. This book discusses as well how computer programs can create plans to satisfy goals. The final chapter deals with computational facilities that support. This book is a valuable resource for cognitive scientists, psychologists, domain experts, computer scientists, instructional designers, expert teachers, and research workers.

Artificial intelligence is revolutionizing the way we learn and teach. In this book, dive into the fascinating world of personalized learning with artificial intelligence and discover how this synergy is transforming education on a global scale. Throughout this book, we explore the fundamental concepts of personalized learning, presenting innovative approaches that empower educators to meet the unique needs of each student. Understand the crucial role of artificial intelligence in customizing educational content, adapting to individual preferences and pace of learning. We will enter the world of AI applied to education, knowing the various specific applications of this technology in educational institutions around the world. Successful case studies will reveal how schools and universities have achieved significant improvements in academic performance, student engagement and school retention. However, we will not ignore the challenges and ethical considerations that come with adopting AI in education. We will explore the barriers to implementing personalized learning with artificial intelligence and discuss how to mitigate algorithmic bias and ensure the privacy of student data. In addition, we will envision the exciting future of personalized learning with AI. Learn about the technological advancements driving this innovative approach and the trends that will shape the educational landscape in the coming years. This book is a must-read for educators, educational managers, researchers, and anyone interested in the future of education. By exploring the transformative possibilities of artificial intelligence in personalized learning, you'll be inspired to drive positive change in the way we learn and teach. Ready to embark on a journey towards personalized, inclusive and innovation-driven education? Come with us and discover how artificial intelligence is shaping the future of education and empowering every student to reach their full potential.

This Festschrift volume, published in celebration of the 50th Anniversary of Artificial Intelligence, includes 34 refereed papers written by leading researchers in the field of Artificial Intelligence. The papers were carefully selected from the invited lectures given at the 50th Anniversary Summit of AI, held at the Centro Stefano Franscini, Monte Verità, Ascona, Switzerland, July 9-14, 2006. The summit provided a venue for discussions on a broad range of topics.

"Artificial Intelligence and Society: Challenges and Opportunities for Social Justice" is a comprehensive book that dives into the intersection between artificial intelligence and social justice issues. Understanding the growing influence of AI in our society, this book seeks to analyze how this technology can both perpetuate and mitigate existing inequalities. Throughout its pages, the book explores crucial topics such as algorithmic bias and its relationship to discrimination, the impact of AI on marginalized communities, equitable access to technology, and the role of ethics and governance in building fair and accountable systems. In addition, examples of positive applications of AI in areas such as health, education and poverty relief are presented, as well as reflections on the transformative potential of this technology. Written by experts in the field, the book offers an in-depth and reflective analysis of the challenges and opportunities AI poses for social justice. With an educational and informative approach, it seeks to encourage the reader to reflect on the ethical and social implications of AI, promoting critical understanding and active engagement. "Artificial Intelligence and Society: Challenges and Opportunities for Social Justice" is an invitation to a journey of discovery, providing a comprehensive and up-to-date overview on the topic. By the end of the reading, it is hoped that the reader will have gained a broader view on the interaction between AI and social justice, as well as the individual and collective role in the quest for a more equitable and inclusive future.

This book constitutes the refereed proceedings of the 9th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2013, held in Paphos, Cyprus, in September/October 2013. The 26 revised full papers presented together with a keynote speech at the main event and 44 papers of 8 collocated workshops were carefully reviewed and selected for inclusion in the volume. The papers of the main event are organized in topical sections on data mining, medical informatics and biomedical engineering, problem solving and scheduling, modeling and decision support systems, robotics, and intelligent signal and image processing.

ARTIFICAL INTELLIGENCE AND DATA ANALYTICS FOR ENERGY EXPLORATION AND PRODUCTION This groundbreaking new book is written by some of the foremost authorities on the application of data science and artificial intelligence techniques in exploration and production in the energy industry, covering the most comprehensive and updated new processes, concepts, and practical applications in the field. The book provides an in-depth treatment of the foundations of Artificial Intelligence (AI) Machine Learning, and Data Analytics (DA). It also includes many of AI-DA applications in oil and gas reservoirs exploration, development, and production. The book covers the basic technical details on many tools used in “smart oil fields”. This includes topics such as pattern recognition, neural networks, fuzzy logic, evolutionary computing, expert systems, artificial intelligence machine learning, human-computer interface, natural language processing, data analytics and next-generation visualization. While theoretical details will be kept to the minimum, these topics are introduced from oil and gas applications viewpoints. In this volume, many case histories from the recent applications of intelligent data to a number of different oil and gas problems are highlighted. The applications cover a wide spectrum of practical problems from exploration to drilling and field development to production optimization, artificial lift, and secondary recovery. Also, the authors demonstrate the effectiveness of intelligent data analysis methods in dealing with many oil and gas problems requiring combining machine and human intelligence as well as dealing with linguistic and imprecise data and rules.

The introduction of Artificial Intelligence (AI) has ignited a fervent academic discourse. AI's role is as both a powerful ally and a potential adversary in education. For instance, ChatGPT is a generative AI which mimics human conversation with impressive precision. Its capabilities span the educational spectrum, from answering questions and generating essays to composing music and coding. Yet, as with any innovation, its advent has sparked a spirited academic dialogue. AI in Language Teaching, Learning, and Assessment seeks to address these concerns with rigor and thoughtfulness. It explores the undeniable drawbacks of AI in language education and offers strategic insights into their prevention. It scrutinizes the resources and safeguards required to ensure the ethical and secure integration of AI in academic settings. This book lays out the multifaceted benefits of incorporating AI into language teaching, learning, and assessment. Its chapters dissect the transformative impact of AI on pedagogy, teaching materials, assessment methodologies, applied linguistics, and the broader landscape of language education development. This book is a valuable resource for language learners, educators, researchers, and scholars alike. It beckons to those who are keen on exploring and implementing AI in education, as well as AI developers and experts seeking to bridge the chasm between technology and language education.

Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed. Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prolog terms and rules (and Prolog facts as special cases); unification; the and-or computation tree induced by a Prolog program and a query; the depth-first, left-to-right traversal of that tree by the standard Prolog interpreter; and built-in predicates such as unification and equality. Subsequent chapters deal with search and representation of graphs in Prolog; backward-chaining methods; truth maintenance systems; and constraint satisfaction. Reasoning with uncertainty, planning and temporal reasoning, and machine learning are also tackled. The book concludes with an assessment of natural language processing and some of the linguistic notions that are easily encoded in Prolog. This monograph will be of interest to both students and practitioners in the fields of AI and computer science.