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| university of illinois artificial intelligence: Social Sensing Dong Wang, Tarek Abdelzaher, Lance Kaplan, 2015-03-23 Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individuals. The title offers theoretical foundations to support emerging data-driven cyber-physical applications and touches on key issues such as privacy. The authors present solutions based on recent research and novel ideas that leverage techniques from cyber-physical systems, sensor networks, machine learning, data mining, and information fusion. Offers a unique interdisciplinary perspective bridging social networks, big data, cyber-physical systems, and reliability Presents novel theoretical foundations for assured social sensing and modeling humans as sensors Includes case studies and application examples based on real data sets Supplemental material includes sample datasets and fact-finding software that implements the main algorithms described in the book |
| university of illinois artificial intelligence: Machine Learning in Industry Shubhabrata Datta, J. Paulo Davim, 2022 This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems. |
| university of illinois artificial intelligence: Artificial Intelligence Reports from the University of Illinois Comtex, Comtex Staff, 1985-03-01 |
| university of illinois artificial intelligence: March of the Machines Kevin Warwick, 2004 While horror films and science fiction have repeatedly warned of robots running amok, Kevin Warwick takes the threats out of the realm of fiction and into the real world, truly giving us something to worry about. Meeting skeptics head on, Warwick goes beyond his penetrating attacks on their assumptions and prejudices about what should be considered as intelligence to reveal what he has already achieved: building robots that communicate in their own language, share experiences, teach each other lessons, and behave as they wish with regard to human beings. Part history of robotics and part futurism, March of the Machines surveys the substantial advances made in artificial intelligence over the past century while looking ahead to an increasingly uneasy relationship between humans and their creations. |
| university of illinois artificial intelligence: Digital Humanities Pedagogy Brett D. Hirsch, 2012 The essays in this collection offer a timely intervention in digital humanities scholarship, bringing together established and emerging scholars from a variety of humanities disciplines across the world. The first section offers views on the practical realities of teaching digital humanities at undergraduate and graduate levels, presenting case studies and snapshots of the authors' experiences alongside models for future courses and reflections on pedagogical successes and failures. The next section proposes strategies for teaching foundational digital humanities methods across a variety of scholarly disciplines, and the book concludes with wider debates about the place of digital humanities in the academy, from the field's cultural assumptions and social obligations to its political visions. (4e de couverture). |
| university of illinois artificial intelligence: Why Literary Periods Mattered Ted Underwood, 2015-01-01 In the mid-nineteenth century, the study of English literature began to be divided into courses that surveyed discrete periods. Since that time, scholars' definitions of literature and their rationales for teaching it have changed radically. But the periodized structure of the curriculum has remained oddly unshaken, as if the exercise of contrasting one literary period with another has an importance that transcends the content of any individual course. Why Literary Periods Mattered explains how historical contrast became central to literary study, and why it remained institutionally central in spite of critical controversy about literature itself. Organizing literary history around contrast rather than causal continuity helped literature departments separate themselves from departments of history. But critics' long reliance on a rhetoric of contrasted movements and fateful turns has produced important blind spots in the discipline. In the twenty-first century, Underwood argues, literary study may need digital technology in particular to develop new methods of reasoning about gradual, continuous change. |
| university of illinois artificial intelligence: An Introduction to Communication and Artificial Intelligence David J. Gunkel, 2020-01-07 Communication and artificial intelligence (AI) are closely related. It is communication – particularly interpersonal conversational interaction – that provides AI with its defining test case and experimental evidence. Likewise, recent developments in AI introduce new challenges and opportunities for communication studies. Technologies such as machine translation of human languages, spoken dialogue systems like Siri, algorithms capable of producing publishable journalistic content, and social robots are all designed to communicate with users in a human-like way. This timely and original textbook provides educators and students with a much-needed resource, connecting the dots between the science of AI and the discipline of communication studies. Clearly outlining the topic's scope, content and future, the text introduces key issues and debates, highlighting the importance and relevance of AI to communication studies. In lively and accessible prose, David Gunkel provides a new generation with the information, knowledge, and skills necessary to working and living in a world where social interaction is no longer restricted to humans. The first work of its kind, An Introduction to Communication and Artificial Intelligence is the go-to textbook for students and scholars getting to grips with this crucial interdisciplinary topic. |
| university of illinois artificial intelligence: Intelligent Support for Computer Science Education Barbara Di Eugenio, Davide Fossati, Nick Green (Engineer), 2021-08 Intelligent Support for Computer Science Education presents the authors' research journey into the effectiveness of human tutoring, with the goal of developing educational technology that can be used to improve introductory Computer Science education at the undergraduate level. Nowadays, Computer Science education is central to the concerns of society, as attested by the penetration of information technology in all aspects of our lives; consequently, in the last few years interest in Computer Science at all levels of schooling, especially at the college level, has been flourishing. However, introductory concepts in Computer Science such as data structures and recursion are difficult for novices to grasp. This book will be of special interest to the Computer Science education community, specifically instructors of introductory courses at the college level, and Advanced Placement (AP) courses at the high school level. Additionally, all the authors' work is relevant to the Educational Technology community, especially to those working in Intelligent Tutoring Systems, their interfaces, and Educational Data Mining, in particular as applied to human-human pedagogical interactions and to user interaction with educational software-- |
| university of illinois artificial intelligence: Lifelong Machine Learning Zhiyuan Chen, Bing Liu, 2018-08-14 Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past helps us learn new things with little data or effort. Lifelong learning aims to emulate this capability, because without it, an AI system cannot be considered truly intelligent. Research in lifelong learning has developed significantly in the relatively short time since the first edition of this book was published. The purpose of this second edition is to expand the definition of lifelong learning, update the content of several chapters, and add a new chapter about continual learning in deep neural networks—which has been actively researched over the past two or three years. A few chapters have also been reorganized to make each of them more coherent for the reader. Moreover, the authors want to propose a unified framework for the research area. Currently, there are several research topics in machine learning that are closely related to lifelong learning—most notably, multi-task learning, transfer learning, and meta-learning—because they also employ the idea of knowledge sharing and transfer. This book brings all these topics under one roof and discusses their similarities and differences. Its goal is to introduce this emerging machine learning paradigm and present a comprehensive survey and review of the important research results and latest ideas in the area. This book is thus suitable for students, researchers, and practitioners who are interested in machine learning, data mining, natural language processing, or pattern recognition. Lecturers can readily use the book for courses in any of these related fields. |
| university of illinois artificial intelligence: Exploring Artificial Intelligence Howard E. Shrobe, 2014-05-12 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. |
| university of illinois artificial intelligence: Artificial Intelligence, Technical Report UIUC-BI-AI. , 1993 |
| university of illinois artificial intelligence: Artificial Intelligence and Conservation Fei Fang, Milind Tambe, Bistra Dilkina, Andrew J. Plumptre, 2019-03-28 Explains how artificial intelligence methods can be used to aid conservation of wildlife, forests, coral reefs, rivers, and other natural resources. |
| university of illinois artificial intelligence: The AI Leader J. Mark Munoz, Al Naqvi, 2021-08-03 The book highlights expert interviews, stories, news events, and academic research impacting our contemporary world in the era of artificial intelligence. This book aims to be a thought-provoking reference guide for corporate executives looking to lead in a world of AI. It is poised to provide readers with game-changing insights on leadership and management in an artificial intelligence economy. Written with an equally educational and fun approach, the book covers practical business strategies that will help managers succeed in an AI world. |
| university of illinois artificial intelligence: Unauthorized Access Robert H. Sloan, Richard Warner, 2013-07-15 Going beyond current books on privacy and security, Unauthorized Access: The Crisis in Online Privacy and Security proposes specific solutions to public policy issues pertaining to online privacy and security. Requiring no technical or legal expertise, the book explains complicated concepts in clear, straightforward language. The authors—two renowned experts on computer security and law—explore the well-established connection between social norms, privacy, security, and technological structure. This approach is the key to understanding information security and informational privacy, providing a practical framework to address ethical and legal issues. The authors also discuss how rapid technological developments have created novel situations that lack relevant norms and present ways to develop these norms for protecting informational privacy and ensuring sufficient information security. Bridging the gap among computer scientists, economists, lawyers, and public policy makers, this book provides technically and legally sound public policy guidance about online privacy and security. It emphasizes the need to make trade-offs among the complex concerns that arise in the context of online privacy and security. |
| university of illinois artificial intelligence: The Economics of Artificial Intelligence Ajay Agrawal, Joshua Gans, Avi Goldfarb, Catherine E. Tucker, 2024-03-14 A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system. |
| university of illinois artificial intelligence: Analysis of Rare Categories Jingrui He, 2014-02-22 In many real-world problems, rare categories (minority classes) play essential roles despite their extreme scarcity. The discovery, characterization and prediction of rare categories of rare examples may protect us from fraudulent or malicious behavior, aid scientific discovery, and even save lives. This book focuses on rare category analysis, where the majority classes have smooth distributions, and the minority classes exhibit the compactness property. Furthermore, it focuses on the challenging cases where the support regions of the majority and minority classes overlap. The author has developed effective algorithms with theoretical guarantees and good empirical results for the related techniques, and these are explained in detail. The book is suitable for researchers in the area of artificial intelligence, in particular machine learning and data mining. |
| university of illinois artificial intelligence: Social Media Analytics for User Behavior Modeling Arun Reddy Nelakurthi, Jingrui He, 2020-01-21 Winner of the Outstanding Academic Title recognition by Choice for the 2020 OAT Awards. The Choice OAT Award represents the highest caliber of scholarly titles that have been reviewed by Choice and conveys the extraordinary recognition of the academic community. In recent years social media has gained significant popularity and has become an essential medium of communication. Such user-generated content provides an excellent scenario for applying the metaphor of mining any information. Transfer learning is a research problem in machine learning that focuses on leveraging the knowledge gained while solving one problem and applying it to a different, but related problem. Features: Offers novel frameworks to study user behavior and for addressing and explaining task heterogeneity Presents a detailed study of existing research Provides convergence and complexity analysis of the frameworks Includes algorithms to implement the proposed research work Covers extensive empirical analysis Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective is a guide to user behavior modeling in heterogeneous settings and is of great use to the machine learning community. |
| university of illinois artificial intelligence: Understanding Machine Learning Shai Shalev-Shwartz, Shai Ben-David, 2014-05-19 Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage. |
| university of illinois artificial intelligence: Artificial Intelligence, Technical Report UIUC-BI-AI-RCV. , 1992 |
| university of illinois artificial intelligence: Distant Horizons Ted Underwood, 2019-02-14 Just as a traveler crossing a continent won’t sense the curvature of the earth, one lifetime of reading can’t grasp the largest patterns organizing literary history. This is the guiding premise behind Distant Horizons, which uses the scope of data newly available to us through digital libraries to tackle previously elusive questions about literature. Ted Underwood shows how digital archives and statistical tools, rather than reducing words to numbers (as is often feared), can deepen our understanding of issues that have always been central to humanistic inquiry. Without denying the usefulness of time-honored approaches like close reading, narratology, or genre studies, Underwood argues that we also need to read the larger arcs of literary change that have remained hidden from us by their sheer scale. Using both close and distant reading to trace the differentiation of genres, transformation of gender roles, and surprising persistence of aesthetic judgment, Underwood shows how digital methods can bring into focus the larger landscape of literary history and add to the beauty and complexity we value in literature. |
| university of illinois artificial intelligence: Artificial Intelligence and the Future of Testing Roy Freedle, 2014-02-24 This volume consists of a series of essays written by experts, most of whom participated in a conference conducted by the Educational Testing Service to explore how current fields of artificial intelligence might contribute to ETS's plans to automate one or more of its testing activities. The papers presented in Artificial Intelligence and the Future of Testing touch on a variety of topics including mathematics tutors, graph comprehension and computer vision, student reasoning and human accessing, modeling software design within a general problem-space architecture, memory organization and retrieval, and natural language systems. Also included: speculation on possible uses each AI specialty might have for a wide number of testing activities, and selective critical commentaries by two eminent AI researchers. As Roy Freedle notes in his introduction, We are at an exciting juncture in applying AI to testing activities. The essays presented in this collection convey some of that excitement, and represent an important step toward the merging of AI and testing -- a powerful combination that has the potential to instruct and inspire. |
| university of illinois artificial intelligence: Machine Learning R.S. Michalski, J.G. Carbonell, T.M. Mitchell, 2013-04-17 The ability to learn is one of the most fundamental attributes of intelligent behavior. Consequently, progress in the theory and computer modeling of learn ing processes is of great significance to fields concerned with understanding in telligence. Such fields include cognitive science, artificial intelligence, infor mation science, pattern recognition, psychology, education, epistemology, philosophy, and related disciplines. The recent observance of the silver anniversary of artificial intelligence has been heralded by a surge of interest in machine learning-both in building models of human learning and in understanding how machines might be endowed with the ability to learn. This renewed interest has spawned many new research projects and resulted in an increase in related scientific activities. In the summer of 1980, the First Machine Learning Workshop was held at Carnegie-Mellon University in Pittsburgh. In the same year, three consecutive issues of the Inter national Journal of Policy Analysis and Information Systems were specially devoted to machine learning (No. 2, 3 and 4, 1980). In the spring of 1981, a special issue of the SIGART Newsletter No. 76 reviewed current research projects in the field. . This book contains tutorial overviews and research papers representative of contemporary trends in the area of machine learning as viewed from an artificial intelligence perspective. As the first available text on this subject, it is intended to fulfill several needs. |
| university of illinois artificial intelligence: Academic Integrity in the Age of Artificial Intelligence Mahmud, Saadia, 2024-02-13 Powerful generative Artificial Intelligence (AI) has defined and transformed our modern era, and the fundamental conceptualization of academia stands at a crossroads. Academic Integrity in the Age of Artificial Intelligence delves deep into the seismic shifts and intricate challenges brought forth by the proliferation of AI technologies, exploring the intricacies between innovation and integrity. The rise of generative AI, exemplified by ChatGPT, has set a cascade of change across diverse sectors, including higher education, medicine, and the arts. This book dissects the multifaceted impact of AI on the academic landscape. With AI's ability to craft text and imagery mirroring human creativity, the lines between authentic scholarship and synthetic deception blur. The book examines the delicate balance between productivity and ethics while weaving a comprehensive tapestry of insights from various stakeholders. From academics grappling with the definition of AI-assisted breaches of academic integrity to policymakers reshaping the future of higher education, this book engages a myriad of voices. It scrutinizes the nascent challenges in assessment design, the urgent need to update antiquated integrity policies, and the importance of research ethics in an AI-driven world. This book is ideal for educators, policymakers, students, and technologists through the complicated terrain of AI ethics. |
| university of illinois artificial intelligence: Inhuman Power Nick Dyer-Witheford, Atle Mikkola Kjøsen, James Steinhoff, 2019 The past several years have brought staggering advances in the field of Artificial Intelligence. And Marxist analysis has to keep up: while machines were always central to Marxist analysis, modern AI is a new kind of machine that Marx could not have anticipated. Inhuman Power explores the relationship between Marxist theory and AI through three approaches, each using the lens of a different Marxist theoretical concept. While the idea of widespread AI tends to be celebrated as much as questioned, a deeper analysis of its reach and potential produces a more complex and disturbing picture than has been identified. Inhuman Power argues that on its current trajectory, AI is likely to render humanity obsolete and that the only way to prevent it is a communist revolution. |
| university of illinois artificial intelligence: Machine Learning Yves Kodratoff, Ryszard S. Michalski, 2014-06-28 Machine Learning: An Artificial Intelligence Approach, Volume III presents a sample of machine learning research representative of the period between 1986 and 1989. The book is organized into six parts. Part One introduces some general issues in the field of machine learning. Part Two presents some new developments in the area of empirical learning methods, such as flexible learning concepts, the Protos learning apprentice system, and the WITT system, which implements a form of conceptual clustering. Part Three gives an account of various analytical learning methods and how analytic learning can be applied to various specific problems. Part Four describes efforts to integrate different learning strategies. These include the UNIMEM system, which empirically discovers similarities among examples; and the DISCIPLE multistrategy system, which is capable of learning with imperfect background knowledge. Part Five provides an overview of research in the area of subsymbolic learning methods. Part Six presents two types of formal approaches to machine learning. The first is an improvement over Mitchell's version space method; the second technique deals with the learning problem faced by a robot in an unfamiliar, deterministic, finite-state environment. |
| university of illinois artificial intelligence: Issues in Artificial Intelligence, Robotics and Machine Learning: 2013 Edition , 2013-05-01 Issues in Artificial Intelligence, Robotics and Machine Learning: 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Expert Systems. The editors have built Issues in Artificial Intelligence, Robotics and Machine Learning: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Expert Systems in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Artificial Intelligence, Robotics and Machine Learning: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/. |
| university of illinois artificial intelligence: Handbook of Artificial Intelligence at Work Martha Garcia-Murillo, Ian MacInnes, Andrea Renda, 2024-02-12 With the advancement in processing power and storage now enabling algorithms to expand their capabilities beyond their initial narrow applications, technology is becoming increasingly powerful. This highly topical Handbook provides a comprehensive overview of the impact of Artificial Intelligence (AI) on work, assessing its impact on an array of economic sectors, their resulting nature of work, and the subsequent policy implications of these changes. |
| university of illinois artificial intelligence: Foundations of Data Science Avrim Blum, John Hopcroft, Ravindran Kannan, 2020-01-23 Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks. |
| university of illinois artificial intelligence: Advanced Artificial Intelligence (Second Edition) Zhongzhi Shi, 2019-08-05 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. |
| university of illinois artificial intelligence: Artificial Intelligence and Learning Futures Stefan Popenici, 2022-11-30 Artificial Intelligence and Learning Futures: Critical Narratives of Technology and Imagination in Higher Education explores the implications of artificial intelligence’s adoption in higher education and the challenges to building sustainable instead of dystopic schooling. As AI becomes integral to both pedagogy and profitability in today’s colleges and universities, a critical discourse on these systems and algorithms is urgently needed to push back against their potential to enable surveillance, control, and oppression. This book examines the development, risks, and opportunities inherent to AI in education and curriculum design, the problematic ideological assumptions of intelligence and technology, and the evidence base and ethical imagination required to responsibly implement these learning technologies in a way that ensures quality and sustainability. Leaders, administrators, and faculty as well as technologists and designers will find these provocative and accessible ideas profoundly applicable to their research, decision-making, and concerns. |
| university of illinois artificial intelligence: Navigating Artificial Intelligence for Cultural Heritage Organisations Lise Jaillant, Claire Warwick, Paul Gooding, Katherine Aske, Glen Layne-Worthey, J. Stephen Downie, 2025-06-12 The question of how artificial intelligence and machine learning should be applied to data in libraries and other cultural institutions is a challenge shared by heritage professionals, computer scientists and digital humanities scholars. As the number of digitised and born-digital records grows, archival practices are looking to automated systems to manage workloads and make cultural records more accessible. AI is playing a crucial role in data management systems within the cultural heritage sector, and information professionals are looking for ways to navigate current challenges and opportunities. Additionally, sector professionals and scholars are benefiting from the many new affordances and innovative research questions offered by using large-scale digital collections as data. Navigating Artificial Intelligence for Cultural Heritage Organisations explores the innovative technologies and approaches to digitised and born-digital records within libraries and archives across the UK and US, and beyond. It brings together chapters from experts across the fields of digital humanities, computer science and information science, alongside professionals within the library and archival sector. The authors explore technologies being applied to digitised and born-digital records within libraries, archives and other heritage organisations, including innovative approaches in computer vision, Chat GPT, and user experience. The volume has been designed to reflect current and state-of-the-art technologies and innovations for the preservation and accessibility of digitised and born-digital records, to help navigate the future of AI for cultural heritage organisations. |
| university of illinois artificial intelligence: Machine Learning Proceedings 1988 John Laird, 2014-05-23 Machine Learning Proceedings 1988 |
| university of illinois artificial intelligence: Readings in Machine Learning Jude W. Shavlik, Thomas Glen Dietterich, 1990 The ability to learn is a fundamental characteristic of intelligent behavior. Consequently, machine learning has been a focus of artificial intelligence since the beginnings of AI in the 1950s. The 1980s saw tremendous growth in the field, and this growth promises to continue with valuable contributions to science, engineering, and business. Readings in Machine Learning collects the best of the published machine learning literature, including papers that address a wide range of learning tasks, and that introduce a variety of techniques for giving machines the ability to learn. The editors, in cooperation with a group of expert referees, have chosen important papers that empirically study, theoretically analyze, or psychologically justify machine learning algorithms. The papers are grouped into a dozen categories, each of which is introduced by the editors. |
| university of illinois artificial intelligence: Advances in Artificial Intelligence Pietro Torasso, 1993-10-05 This book contains 22 long papers and 13 short ones selected for the Scientific Track of the Third Congress of the Italian Association for Artificial Intelligence. The long papers report completed work whereas the short papers are mainly devoted to ongoing research. The papers report significant work carried out in the different subfields of artificial intelligence not only in Italy but also elsewhere: 8 of the papers come from outside Italy, with 2 from the United States and 1 eachfrom Australia, Austria, Germany, The Netherlands, Spain, and Turkey. The papers in the book are grouped into parts on: automated reasoning; cognitive models; connectionist models and subsymbolic approaches; knowledge representation and reasoning; languages, architectures and tools for AI; machine learning; natural language; planning and robotics; and reasoning about physical systems and artifacts. |
| university of illinois artificial intelligence: Foundational Issues in Artificial Intelligence and Cognitive Science Mark H. Bickhard, L. Terveen, 1996-10-04 The book focuses on a conceptual flaw in contemporary artificial intelligence and cognitive science. Many people have discovered diverse manifestations and facets of this flaw, but the central conceptual impasse is at best only partially perceived. Its consequences, nevertheless, visit themselves asdistortions and failures of multiple research projects - and make impossible the ultimate aspirations of the fields.The impasse concerns a presupposition concerning the nature of representation - that all representation has the nature of encodings: encodingism. Encodings certainly exist, butencodingism is at root logically incoherent; any programmatic research predicted on it is doomed too distortion and ultimate failure.The impasse and its consequences - and steps away from that impasse - are explored in a large number of projects and approaches. These include SOAR, CYC, PDP, situated cognition, subsumption architecture robotics, and the frame problems - a general survey of the current research in AI and Cognitive Science emerges.Interactivism, an alternative model of representation, is proposed and examined. |
| university of illinois artificial intelligence: Artificial Intelligence Richard E. Neapolitan, Xia Jiang, 2018-03-12 The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding. Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more. |
| university of illinois artificial intelligence: Machine Learning Proceedings 1992 Peter Edwards, Derek Sleeman, 2014-06-28 Machine Learning Proceedings 1992 |
| university of illinois artificial intelligence: Modern Robotics Kevin M. Lynch, Frank C. Park, 2017-05-25 This introduction to robotics offers a distinct and unified perspective of the mechanics, planning and control of robots. Ideal for self-learning, or for courses, as it assumes only freshman-level physics, ordinary differential equations, linear algebra and a little bit of computing background. Modern Robotics presents the state-of-the-art, screw-theoretic techniques capturing the most salient physical features of a robot in an intuitive geometrical way. With numerous exercises at the end of each chapter, accompanying software written to reinforce the concepts in the book and video lectures aimed at changing the classroom experience, this is the go-to textbook for learning about this fascinating subject. |
| university of illinois artificial intelligence: Artificial Intelligence, Technical Report UIUC-BI-AI-DSS. , 1992 |
| university of illinois artificial intelligence: Artificial Intelligence Planning Systems James Hendler, 1992 |
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Aug 18, 2024 · The university was connected to the Kwame Nkrumah University of Science and Technology, the University of Cape Coast, and the University of Ghana before obtaining a …
What Are University Entrance Exams? Your Complete Guide
Mar 26, 2024 · University entrance exams, also known as college entrance exams or standardized tests, are assessments designed to evaluate a student’s readiness and …
