Artificial Intelligence and Machine Learning for Open-world Novelty

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Author :
Publisher : Elsevier
ISBN 13 : 0323999298
Total Pages : 378 pages
Book Rating : 4.98/5 ( download)

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Book Synopsis Artificial Intelligence and Machine Learning for Open-world Novelty by :

Download or read book Artificial Intelligence and Machine Learning for Open-world Novelty written by and published by Elsevier. This book was released on 2024-02-20 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Computers, Volume presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on Contains novel subject matter that is relevant to computer science Includes the expertise of contributing authors Presents an easy to comprehend writing style

A Unifying Framework for Formal Theories of Novelty

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Author :
Publisher : Springer Nature
ISBN 13 : 3031330544
Total Pages : 119 pages
Book Rating : 4.44/5 ( download)

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Book Synopsis A Unifying Framework for Formal Theories of Novelty by : Terrance Boult

Download or read book A Unifying Framework for Formal Theories of Novelty written by Terrance Boult and published by Springer Nature. This book was released on 2023-08-01 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the first unified formalization for defining novelty across the span of machine learning, symbolic-reasoning, and control and planning-based systems. Dealing with novelty, things not previously seen by a system, is a critical issue for building vision-systems and general intelligent systems. The book presents examples of using this framework to define and evaluate in multiple domains including image recognition image-based open world learning, hand-writing and author analysis, CartPole Control, Image Captioning, and Monopoly. Chapters are written by well-known contributors to this new and emerging field. In addition, examples are provided from multiple areas, such as machine-learning based control problems, symbolic reasoning, and multi-player games.

Multi-disciplinary Trends in Artificial Intelligence

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Author :
Publisher : Springer Nature
ISBN 13 : 3030802531
Total Pages : 202 pages
Book Rating : 4.30/5 ( download)

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Book Synopsis Multi-disciplinary Trends in Artificial Intelligence by : Phatthanaphong Chomphuwiset

Download or read book Multi-disciplinary Trends in Artificial Intelligence written by Phatthanaphong Chomphuwiset and published by Springer Nature. This book was released on 2021-06-26 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2021, held online in July 2021. The 13 full papers and 3 short papers presented were carefully reviewed and selected from 33 submissions. They cover a wide range of topics in theory, methods, and tools in AI sub-areas such as cognitive science, computational philosophy, computational intelligence, game theory, machine learning, multi-agent systems, natural language, representation and reasoning, data mining, speech, computer vision and the Web as well as their applications in big data, bioinformatics, biometrics, decision support, knowledge management, privacy, recommender systems, security, software engineering, spam filtering, surveillance, telecommunications, Web services, and IoT.

AI 2023: Advances in Artificial Intelligence

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Publisher : Springer Nature
ISBN 13 : 9819983916
Total Pages : 509 pages
Book Rating : 4.19/5 ( download)

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Book Synopsis AI 2023: Advances in Artificial Intelligence by : Tongliang Liu

Download or read book AI 2023: Advances in Artificial Intelligence written by Tongliang Liu and published by Springer Nature. This book was released on 2023-11-26 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNAI 14471-14472 constitutes the refereed proceedings of the 36th Australasian Joint Conference on Artificial Intelligence, AI 2023, held in Brisbane, QLD, Australia during November 28 – December 1, 2023. The 23 full papers presented together with 59 short papers were carefully reviewed and selected from 213 submissions. They are organized in the following topics: computer vision; deep learning; machine learning and data mining; optimization; medical AI; knowledge representation and NLP; explainable AI; reinforcement learning; and genetic algorithm..

General Video Game Artificial Intelligence

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Publisher : Springer Nature
ISBN 13 : 3031021223
Total Pages : 177 pages
Book Rating : 4.20/5 ( download)

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Book Synopsis General Video Game Artificial Intelligence by : Diego Pérez Liébana

Download or read book General Video Game Artificial Intelligence written by Diego Pérez Liébana and published by Springer Nature. This book was released on 2022-05-31 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on general video game playing aims at designing agents or content generators that can perform well in multiple video games, possibly without knowing the game in advance and with little to no specific domain knowledge. The general video game AI framework and competition propose a challenge in which researchers can test their favorite AI methods with a potentially infinite number of games created using the Video Game Description Language. The open-source framework has been used since 2014 for running a challenge. Competitors around the globe submit their best approaches that aim to generalize well across games. Additionally, the framework has been used in AI modules by many higher-education institutions as assignments, or as proposed projects for final year (undergraduate and Master's) students and Ph.D. candidates. The present book, written by the developers and organizers of the framework, presents the most interesting highlights of the research performed by the authors during these years in this domain. It showcases work on methods to play the games, generators of content, and video game optimization. It also outlines potential further work in an area that offers multiple research directions for the future.

Artificial Intelligence for Industries of the Future

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Author :
Publisher : Springer Nature
ISBN 13 : 3031190394
Total Pages : 165 pages
Book Rating : 4.91/5 ( download)

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Book Synopsis Artificial Intelligence for Industries of the Future by : Mayank Kejriwal

Download or read book Artificial Intelligence for Industries of the Future written by Mayank Kejriwal and published by Springer Nature. This book was released on 2022-11-25 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a brief synthesis of the known implementations, opportunities and challenges at the intersection of artificial intelligence (AI) and modern industry beyond the big-four companies that traditionally consume and produce such advanced technology: Facebook, Amazon, Microsoft and Google. With this information, the author also makes some reasonable claims about the role of AI in future industries. The book draws on a broad range of material, including reports from consulting firms, published surveys, academic papers and books, and expert knowledge available to the author due to numerous collaborations in academia and industry on AI. It is rigorous rather than speculative, drawing on known findings and expert summaries, where available. This provides industry leaders and other interested stakeholders with an accessible review of contemporary perspectives on AI’s forward-looking role in industry as well as a clarifying guide on the major issues that companies are likely to face as they commence on this exciting path. Examines the likely role of AI in industries of the future, both known and unknown Presents use-cases of AI currently being explored across Big Tech, multi-national corporations and start-ups Explores the regulation of AI and its potential impacts on the workforce

Proceedings of 2023 Chinese Intelligent Automation Conference

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Author :
Publisher : Springer Nature
ISBN 13 : 9819961874
Total Pages : 854 pages
Book Rating : 4.70/5 ( download)

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Book Synopsis Proceedings of 2023 Chinese Intelligent Automation Conference by : Zhidong Deng

Download or read book Proceedings of 2023 Chinese Intelligent Automation Conference written by Zhidong Deng and published by Springer Nature. This book was released on 2023-10-24 with total page 854 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents selected research papers from the 2023 Chinese Intelligent Automation Conference (CIAC2023), held in Nanjing, China, on October 2-5, 2023. It covers a wide range of topics including intelligent control, robotics, artificial intelligence, pattern recognition, unmanned systems, IoT, and machine learning. It includes original research and the latest advances in the field of intelligent automation. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in this field.

The AI Commander

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Author :
Publisher : Oxford University Press
ISBN 13 : 0198892187
Total Pages : 241 pages
Book Rating : 4.82/5 ( download)

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Book Synopsis The AI Commander by : James Johnson

Download or read book The AI Commander written by James Johnson and published by Oxford University Press. This book was released on 2024-01-11 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the largely neglected question of how the fusion of machines into the war machine will affect the human condition of warfare. It emphasizes the "mind" and the mechanisms of thought (intelligence, consciousness, emotion, memory, experience, etc.) to consider the effects of AI and autonomy on the human condition of war.

Rebooting AI

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Author :
Publisher : Vintage
ISBN 13 : 052556604X
Total Pages : 290 pages
Book Rating : 4.45/5 ( download)

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Book Synopsis Rebooting AI by : Gary Marcus

Download or read book Rebooting AI written by Gary Marcus and published by Vintage. This book was released on 2020-08-25 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a robust artificial intelligence that can make our lives better. “Finally, a book that tells us what AI is, what AI is not, and what AI could become if only we are ambitious and creative enough.” —Garry Kasparov, former world chess champion and author of Deep Thinking Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.

Lifelong Machine Learning, Second Edition

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Author :
Publisher : Springer Nature
ISBN 13 : 3031015819
Total Pages : 187 pages
Book Rating : 4.16/5 ( download)

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Book Synopsis Lifelong Machine Learning, Second Edition by : Zhiyuan Sun

Download or read book Lifelong Machine Learning, Second Edition written by Zhiyuan Sun and published by Springer Nature. This book was released on 2022-06-01 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.