5 sterreichische Artificial Intelligence Tagung

Die Arbeit an diesem Projekt wurde zum Teil vom COST-13 Projekt Machine Learning and Knowledge Acquisition gefördert. Literatur Anderson, J.R. (1985). Knowledge Compilation: The General Learning Mechanism. In R.Michalski, J.Carbonell, ...

5    sterreichische Artificial Intelligence Tagung

Die 5. Österreichische Artificial-Intelligence-Tagung setzt sich zusammen aus wissenschaftlichem Programm, Workshops und Tutorials. Der wissenschaftlich orientierte Teil des Tagungsprogramms umfa€t sowohl eingeladene als auch begutachtete Vorträge zu den Themen Qualitatives Schlie€en, Methodik Wissensbasierter Systeme und deren Anwendung, Logik/Deduktion, Natürlichsprachliche Systeme, Lernen und Kognition. Zum Informationsaustausch waren zusätzlich Workshops zur Weiterbildung vorgesehen. Besonders das Thema "Philosophie und KI" demonstrierte das allgemeine Interesse. Dies soll mit Beiträgen dokumentiert werden, die einen Überblick über Berührungspunkte der KI mit philosophischen Strömungen bieten und auch den Einflu€ der KI als Teil der Informatik auf das philosophische Weltbild verdeutlichen. Ebenfalls repräsentative Beiträge wurden zu den Workshops "Konnektionismus", "Qualitatives Schlie€en" und "Begriffsbildung/-modellierung" ausgewählt.

4 sterreichische Artificial Intelligence Tagung

Österreichische Artificial-Intelligence-Tagung Wiener Workshop Wissensbasierte Sprachverarbeitung Wien, 29.-31. August 1988 Proceedings Springer-Verlag Berlin Heidelberg New York London Paris Tokyo Herausgeber Harald Trost Universität ...

4    sterreichische Artificial Intelligence Tagung

Dieser Band ist der Bericht von einer Tagung zum Thema Verarbeitung natürlicher Sprache am Computer. Er enthält Lang- und Kurzbeiträge führender Wissenschaftler aus dem deutschsprachigen Raum sowie aus den USA. Alle Teilbereiche der Sprachverarbeitung wie Morphologie, Parsing, semantische Analyse und Verarbeitung gesprochener Sprache werden abgedeckt. Das Ziel der Tagung war eine Darstellung des Themas, die die Verarbeitung der deutschen Sprache in den Mittelpunkt rückt. So behandeln die Beiträge einige speziell für das Deutsche entwickelte Systeme, sowie Adaptierungen von für das Englische bewährten Formalismen für die Anwendung auf das Deutsche. Dadurch liefert dieses Buch zum ersten Mal eine kompakte Zusammenstellung der neuesten Forschungsergebnisse unter diesem speziellen Gesichtspunkt.

What Every Engineer Should Know about Artificial Intelligence

A Definition of Artificial Intelligence Donald Knuth once said , " The difference between art and science is that science is what we can program into a computer . All else is art . " Artificial intelligence covers so much intellectual ...

What Every Engineer Should Know about Artificial Intelligence

AI expert and consultant William Taylor provides a practical explanation of the parts of AI research that are ready for use by anyone with an engineering degree and that can help engineers do their jobs better.

Life 3 0

'This is the most important conversation of our time, and Tegmark's thought-provoking book will help you join it' Stephen Hawking THE INTERNATIONAL BESTSELLER.

Life 3 0

'This is the most important conversation of our time, and Tegmark's thought-provoking book will help you join it' Stephen Hawking THE INTERNATIONAL BESTSELLER. DAILY TELEGRAPH AND THE TIMES BOOKS OF THE YEAR SELECTED AS ONE OF BARACK OBAMA'S FAVOURITE BOOKS OF 2018 AI is the future - but what will that future look like? Will superhuman intelligence be our slave, or become our god? Taking us to the heart of the latest thinking about AI, Max Tegmark, the MIT professor whose work has helped mainstream research on how to keep AI beneficial, separates myths from reality, utopias from dystopias, to explore the next phase of our existence. How can we grow our prosperity through automation, without leaving people lacking income or purpose? How can we ensure that future AI systems do what we want without crashing, malfunctioning or getting hacked? Should we fear an arms race in lethal autonomous weapons? Will AI help life flourish as never before, or will machines eventually outsmart us at all tasks, and even, perhaps, replace us altogether? 'This is a rich and visionary book and everyone should read it' The Times

Artificial Intelligence

Featuring the viewpoint of expert members of the IFIP Technical Committee 12, its Working Groups and their colleagues, this book provides an international perspective on recent and future directions in this significant field.

Artificial Intelligence

Featuring the viewpoint of expert members of the IFIP Technical Committee 12, its Working Groups and their colleagues, this book provides an international perspective on recent and future directions in this significant field.

Encyclopedia of Artificial Intelligence

When data from users is available, systems use often machine learning to optimize their results. Artificial Intelligence Methods in Information Retrieval This article describes the most prominent approaches to apply artificial ...

Encyclopedia of Artificial Intelligence

"This book is a comprehensive and in-depth reference to the most recent developments in the field covering theoretical developments, techniques, technologies, among others"--Provided by publisher.

AI 2001 Advances in Artificial Intelligence

14th International Joint Conference on Artificial Intelligence, Adelaide, Australia, December 10-14, 2001, Proceedings Australian Joint Conference on Artificial Intelligence 2001 Adelaide, Markus Stumptner Mike Brooks, Dan Corbett, ...

AI 2001  Advances in Artificial Intelligence

This book constitutes the refereed proceedings of the 14th Australian Joint Conference on Artificial Intelligence, AI 2001, held in Adelaide, Australia, in December 2001. The 55 revised full papers presented together with one invited contribution were carefully reviewed and selected from a total of 100 submissions. The papers cover the whole range of artificial intelligence from theoretical and foundational issues to advanced applications in a variety of fields.

Artificial Intelligence for Audit Forensic Accounting and Valuation

Practical,insightful,and forward-looking, Artificial Intelligence for Audit, ForensicAccounting, and Valuation: A Strategic Perspective provides readerswithastep-by-step roadmap to understanding artificial intelli- ...

Artificial Intelligence for Audit  Forensic Accounting  and Valuation

Strategically integrate AI into your organization to compete in the tech era The rise of artificial intelligence is nothing short of a technological revolution. AI is poised to completely transform accounting and auditing professions, yet its current application within these areas is limited and fragmented. Existing AI implementations tend to solve very narrow business issues, rather than serving as a powerful tech framework for next-generation accounting. Artificial Intelligence for Audit, Forensic Accounting, and Valuation provides a strategic viewpoint on how AI can be comprehensively integrated within audit management, leading to better automated models, forensic accounting, and beyond. No other book on the market takes such a wide-ranging approach to using AI in audit and accounting. With this guide, you’ll be able to build an innovative, automated accounting strategy, using artificial intelligence as the cornerstone and foundation. This is a must, because AI is quickly growing to be the single competitive factor for audit and accounting firms. With better AI comes better results. If you aren’t integrating AI and automation in the strategic DNA of your business, you’re at risk of being left behind. See how artificial intelligence can form the cornerstone of integrated, automated audit and accounting services Learn how to build AI into your organization to remain competitive in the era of automation Go beyond siloed AI implementations to modernize and deliver results across the organization Understand and overcome the governance and leadership challenges inherent in AI strategy Accounting and auditing firms need a comprehensive framework for intelligent, automation-centric modernization. Artificial Intelligence for Audit, Forensic Accounting, and Valuation delivers just that—a plan to evolve legacy firms by building firmwide AI capabilities.

Transforming Management Using Artificial Intelligence Techniques

National strategy for artificial intelligence . Discussion Paper June 2018 . Agrawal , R. , & Gupta , N. ( 2017 ) Educational data mining review : Teaching enhancement . S. Tamane , V.K. Solanki , N. Dey ( eds . ) ...

Transforming Management Using Artificial Intelligence Techniques

Transforming Management Using Artificial Intelligence Techniques redefines management practices using artificial intelligence (AI) by providing a new approach. It offers a detailed, well-illustrated treatment of each topic with examples and case studies, and brings the exciting field to life by presenting a substantial and robust introduction to AI in a clear and concise manner. It provides a deeper understanding of how the relevant aspects of AI impact each other’s efficacy for better output. It’s a reliable and accessible one-step resource that introduces AI; presents a full examination of applications; provides an understanding of the foundations; examines education powered by AI, entertainment, home and service robots, healthcare re-imagined, predictive policing, space exploration; and so much more, all within the realm of AI. This book will feature: Uncovering new and innovative features of AI and how it can help in raising economic efficiency at both micro- and macro levels Both the literature and practical aspects of AI and its uses This book summarizing key concepts at the end of each chapter to assist reader comprehension Case studies of tried and tested approaches to resolutions of typical problems Ideal for both teaching and general-knowledge purposes. This book will also simply provide the topic of AI for the readers, aspiring researchers and practitioners involved in management and computer science, so they can obtain a high-level of understanding of AI and managerial applications.

BASICS OF ARTIFICIAL INTELLIGENCE MACHINE LEARNING

Artificial. Intelligence: Introduction. Hi Welcome to the basics of AI – for beginners. As you know AI as the word suggests, Artificial Intelligence also known as Machine Intelligence is the Intelligence predicted of the machine through ...

BASICS OF ARTIFICIAL INTELLIGENCE   MACHINE LEARNING

The concept of Artificial Intelligence (AI) & Machine Learning (ML) has been in practice for over years with the advent of technological progress. Over time, it has blended our lives through nearly every narration of learning, teaching, enjoyment, normal routine operations and what not. The aspect delivers a common understanding of the topics with reference to it making an impact on our lives, with a better framework of technology affecting our lives in particular. Let us look up to science for a change to be brought about in us. Let us create awareness of making technology available to people, in a broader sense. As that happens, people who are responsible need to be told about the use and misuse of the same. As we lead our lives, we come across the fact that AI, Robotics and Learning Machines seem to be the household topic of discussion. Earlier, AI was perceived to be reserved for only ‘Geniuses’ or ‘Researchers’ or the ‘computer’ community, but it very aptly integrates and impacts each and every aspect of our lives. Knowingly or unknowingly, it has become intellectually influential in shaping our thoughts, actions and the day-to-day chores.

Artificial Intelligence for Big Data

Complete guide to automating Big Data solutions using Artificial Intelligence techniques Anand Deshpande, Manish Kumar ... In 1990, there were significant demonstrations of machine learning algorithms supported by case-based reasoning ...

Artificial Intelligence for Big Data

Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.

Predictive Policing and Artificial Intelligence

Since extant algorithms can only perform a single or a minimal range of functions that could possibly be described as 'intelligent', computer scientists refer to this as 'narrow' intelligence or 'Artificial Narrow Intelligence' (ANI) ...

Predictive Policing and Artificial Intelligence

This edited text draws together the insights of numerous worldwide eminent academics to evaluate the condition of predictive policing and artificial intelligence (AI) as interlocked policy areas. Predictive and AI technologies are growing in prominence and at an unprecedented rate. Powerful digital crime mapping tools are being used to identify crime hotspots in real-time, as pattern-matching and search algorithms are sorting through huge police databases populated by growing volumes of data in an eff ort to identify people liable to experience (or commit) crime, places likely to host it, and variables associated with its solvability. Facial and vehicle recognition cameras are locating criminals as they move, while police services develop strategies informed by machine learning and other kinds of predictive analytics. Many of these innovations are features of modern policing in the UK, the US and Australia, among other jurisdictions. AI promises to reduce unnecessary labour, speed up various forms of police work, encourage police forces to more efficiently apportion their resources, and enable police officers to prevent crime and protect people from a variety of future harms. However, the promises of predictive and AI technologies and innovations do not always match reality. They often have significant weaknesses, come at a considerable cost and require challenging trade- off s to be made. Focusing on the UK, the US and Australia, this book explores themes of choice architecture, decision- making, human rights, accountability and the rule of law, as well as future uses of AI and predictive technologies in various policing contexts. The text contributes to ongoing debates on the benefits and biases of predictive algorithms, big data sets, machine learning systems, and broader policing strategies and challenges. Written in a clear and direct style, this book will appeal to students and scholars of policing, criminology, crime science, sociology, computer science, cognitive psychology and all those interested in the emergence of AI as a feature of contemporary policing.

AI 2003 Advances in Artificial Intelligence

In: Proceedings of the Thirteenth International Conference on Machine Learning, Morgan Kaufmann Publishers, Inc., San Francisco, CA(1996)105–112, 453, 454 Kohavi, R.: Scaling up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree ...

AI 2003  Advances in Artificial Intelligence

Consider the problem of a robot (algorithm, learning mechanism) moving along the real line attempting to locate a particular point ? . To assist the me- anism, we assume that it can communicate with an Environment (“Oracle”) which guides it with information regarding the direction in which it should go. If the Environment is deterministic the problem is the “Deterministic Point - cation Problem” which has been studied rather thoroughly [1]. In its pioneering version [1] the problem was presented in the setting that the Environment could charge the robot a cost which was proportional to the distance it was from the point sought for. The question of having multiple communicating robots locate a point on the line has also been studied [1, 2]. In the stochastic version of this problem, we consider the scenario when the learning mechanism attempts to locate a point in an interval with stochastic (i. e. , possibly erroneous) instead of deterministic responses from the environment. Thus when it should really be moving to the “right” it may be advised to move to the “left” and vice versa. Apart from the problem being of importance in its own right, the stoch- tic pointlocationproblemalsohas potentialapplications insolvingoptimization problems. Inmanyoptimizationsolutions–forexampleinimageprocessing,p- tern recognition and neural computing [5, 9, 11, 12, 14, 16, 19], the algorithm worksits wayfromits currentsolutionto the optimalsolutionbasedoninfor- tion that it currentlyhas. A crucialquestionis oneof determining the parameter whichtheoptimizationalgorithmshoulduse.

Artificial Intelligence in Engineering Design

[3] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] Dechter, R. and Pearl, J ., “Network-based heuristics for constraint satisfaction problems,” Artificial Intelligence, Vol. 34, pp. 1-38, 1988.

Artificial Intelligence in Engineering Design

Artificial Intelligence in Engineering Design is a three-volume edited collection of key papers from the field of AI and design, aimed at providing a state-of-the art description of the field, and focusing on how ideas and methods from artificial intelligence can help engineers in the design of physical artifacts and processes. The books survey a wide variety of applications in the areas of civil, chemical, electrical, computer, VLSI, and mechanical engineering.

New Frontiers in Artificial Intelligence

The annual conference of JSAI (Japan Society for Artificial Intelligence) is one of the key and representative domestic meetings in the field of intelligent information technology. In particular, award papers in this conference have an ...

New Frontiers in Artificial Intelligence

This book presents the joint post-proceedings of five international workshops organized by the Japanese Society for Artificial Intelligence, during the 19th Annual Conference JSAI 2005. The volume includes 5 award winning papers of the main conference, along with 40 revised full workshop papers, covering such topics as logic and engineering of natural language semantics, learning with logics, agent network dynamics and intelligence, conversational informatics and risk management systems with intelligent data analysis.

MICAI 2002 Advances in Artificial Intelligence

Second Mexican International Conference on Artificial Intelligence Merida, Yucatan, Mexico, April 22-26, 2002 Proceedings Carlos Coello Coello, Alvaro de Albornoz, Luis E. Sucar, Osvaldo C. Battistutti. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

MICAI 2002  Advances in Artificial Intelligence

This book constitutes the refereed proceedings of the Second Mexican International Conference on Artificial Intelligence, MICAI 2002, held in Mérida, Yucatán, Mexico in April 2002. The 56 revised full papers presented were carefully reviewed and selected from more than 85 submissions from 17 countries. The papers are organized in topical sections on robotics and computer vision, heuristic search and optimization, speech recognition and natural language processing, logic, neural networks, machine learning, multi-agent systems, uncertainty management, and AI tools and applications.

Liability for Artificial Intelligence and the Internet of Things

Data and the ability of making use of them is the key for both develop‐ing new informatics tools, such as analytics and predictive coding, and feeding the creation of artificial intelligence (AI) and its actual operation.

Liability for Artificial Intelligence and the Internet of Things

Wissenschaftler und Praktiker aus mehreren europäischen Ländern befassen sich in dem Band mit Grundfragen der Haftung für die Herstellung und Verwendung künstlicher Intelligenz. Sie entwickeln vor dem Hintergrund der Gesetzgebungsinitiativen auf nationaler und europäischer Ebene (wie der Resolution des Europäischen Parlaments über "Civil Law Rules on Robotics") Analysen und Lösungsvorschläge zur Fortentwicklung der Produkthaftung, zur Anpassung traditioneller Konzepte des Deliktsrechts und zur Funktion von Gefährdungshaftungstatbeständen. Die Reihe der "Münster Colloquia on EU Law and the Digital Economy" wendet sich damit einer vordringlichen Herausforderung für Rechtswissenschaft und Praxis zu. Mit Beiträgen von Cristina Amato, Georg Borges, Jean-Sébastien Borghetti, Giovanni Comandé, Ernst Karner, Bernhard Koch, Sebastian Lohsse, Eva Lux, Miquel Martín-Casals, Reiner Schulze, Gerald Spindler, Dirk Staudenmayer, Gerhard Wagner, Herbert Zech

AI IA 2001 Advances in Artificial Intelligence

Proc. of the 13th Int. Joint Conf. on Artificial Intelligence, (Chambery, France, 1993), pp. 937-943. 6. M. Botta and R. Piola (2000). Refining Numerical Constants in Structured First Order Logic Theories. Machine Learning Journal, 38, ...

AI IA 2001  Advances in Artificial Intelligence

This book constitutes the refereed proceedings of the scientific track of the 7th Congress of the Italian Association for Artificial Intelligence, AI*IA 2001, held in Bari, Italy, in September 2001. The 25 revised long papers and 16 revised short papers were carefully reviewed and selected for inclusion in the volume. The papers are organized in topical sections on machine learning; automated reasoning; knowledge representation; multi-agent systems; natural language processing; perception, vision, and robotics; and planning and scheduling.

MICAI 2004 Advances in Artificial Intelligence

Third Mexican International Conference on Artificial Intelligence, Mexico City, Mexico, April 26-30, 2004, Proceedings Raúl Monroy, Gustavo Arroyo-Figueroa, Luis Enrique Sucar, Humberto Sossa. Section 3). Besides, the hybrid approach ...

MICAI 2004  Advances in Artificial Intelligence

representative of the main current area of interest within the AI community.

Artificial Intelligence How Computers Think

by putting automation using artificial intelligence, where many aspects need to be accounted for in bringing customers a complete engagement loop to bring a significant impact in the revenue of the business. It is no longer sufficient ...

Artificial Intelligence  How Computers Think

We have seen lots of books, blogs, YouTube channels, and other resources on Artificial Intelligence. We decided to write this book because there are very few of them on the internet that connects essential learning to industry requirements. After experiencing various shades of academia and industry, we thought of bringing our experience for others.