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Bayesian Networks and Decision Graphs
Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence, detecting conflicts in the evidence entered into the network, determining optimal strategies, analyzing for relevance, and performing sensitivity analysis. The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams.It contians two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems.
Banking on (artificial) intelligence : Navigating the realities of ai in financial services
Provides a tailored overview of what AI specifically means for financial services, a highly regulated yet also disrupted industry. it investigates the current state of AI applications in financial services today along with the state of funding and partnerships between tech and banking industries. it also examines the key pillars of responsible AI and the importance of keeping humans in the loop. the book takes a deep dive into the use cases in the financial services industry, the challenges and opportunities, and the fragmented regulatory landscape. how can we effectively assess risks, and balance innovation and customer centricity with trust in AI in financial services? can smaller organizations reap the benefits of the technology? how can institutions deploy AI responsibly and securely, and promote a fairer and more equitable future for more people?
Autonomous intelligent systems : Multi-agents and data mining ; 2nd International workshop, AIS-ADM 2007, St. Petersburg, Russia, June 3-5, 2007, Proceedings
MAS offiers powerful metaphors for information system conceptualization, a range of new techniques, and technologies specifically focused on the design and implementation of lar- scale open distributed intelligent systems. KDD also provides intelligent inf- mation technology with powerful ideas, algorithms, and software means to help cope with the main problem of artificial intelligence, formulated in the we- known question “Where does the knowledge come from?”, thus actually making modern applications intelligent and adaptive. The evident recent trend in both science and industry is to integrate and take advantage of both technologies. The existing experience with combined application of multi-agent technology to design architectures of distributed (- erarchical and peer-to-peer) data mining and KDD systems, as well as the u- lization of data mining and KDD achievements to provide enhanced intelligence of MAS, confirms the fact that both technologies are capable of mutual enri- ment and their integrateduse may result in intelligent information systems with new emergent properties.
Automating business modelling : A guide to using logic to represent Informal methods and support reasoning
Enterprise Modelling (EM) methods are frequently used by entrepreneurs as an analysis tool for describing and redesigning their businesses. The resulting product, an enterprise model, is commonly used as a blueprint for reconstructing organizations and such effort is often a part of business process re-engineering and improvement initiatives. Automating Business Modelling describes different techniques of providing automated support for enterprise modelling methods and introduces universally used approaches. A running example of a business modelling method is included; providing a framework and detailed explanation as to how to construct automated support for modelling, allowing readers to follow the method to create similar support. Suitable for senior undergraduates and postgraduates of Business Studies, Computer Science and Artificial Intelligence, practitioners in the fields of Knowledge Management, Enterprise Modelling and Software Engineering, this book offers insight and know-how to both student and professional.
Automatic video editor
Searching in a large database of videos is one of the challenges faced by the user today as most of the results are inaccurate or correct. In our project, we worked on developing a system that receives the search word from the user and searches for it among a large number of videos using MSR-VTT dataset and COCO data set based on the elements that we see inside the video. Entered by the user. We have also worked on adding other options that the user can benefit from in modifying the videos, such as entering a black and white video clip and returning the result in color. The user can also enter a low-resolution video clip, and the system improves the accuracy of the video and sends it.
Automatic Quantum Computer Programming : A Genetic Programming Approach
Computer science will be radically transformed if ongoing efforts to build large-scale quantum computers eventually succeed and if the properties of these computers meet optimistic expectations. Nevertheless, computer scientists still lack a thorough understanding of the power of quantum computing, and it is not always clear how best to utilize the power that it is understood. This dilemma exists because quantum algorithms are difficult to grasp and even more difficult to write. Despite large-scale international efforts, only a few important quantum algorithms are documented, leaving many essential questions about the potential of quantum algorithms unanswered.
Automated technology for verification and analysis ; 18th International Symposium, ATVA 2020, Hanoi, Vietnam, October 19–23, 2020, Proceedings
This book constitutes the refereed proceedings of the 18th International Symposium on Automated Technology for Verification and Analysis, ATVA 2020, held in Hanoi, Vietnam, in October 2020. The 27 regular papers presented together with 5 tool papers and 2 invited papers were carefully reviewed and selected from 75 submissions.
Automated machine learning : Methods, systems, challenges
This book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself.
Automated deduction – CADE 28 ; 28th International Conference on automated deduction, Virtual Event, July 12–15, 2021, Proceedings
This book constitutes the proceeding of the 28th International Conference on Automated Deduction, CADE 28, held virtually in July 2021. The 29 full papers and 7 system descriptions presented together with 2 invited papers were carefully reviewed and selected from 76 submissions. CADE is the major forum for the presentation of research in all aspects of automated deduction, including foundations, applications, implementations, and practical experience. The papers are organized in the following topics: Logical foundations; theory and principles; implementation and application; ATP and AI; and system descriptions.
Augmented reality, virtual reality, and computer graphics ; 7th International Conference, AVR 2020, Lecce, Italy, September 7–10, 2020, Proceedings, Part II
The 2-volume set LNCS 12242 and 12243 constitutes the refereed proceedings of the 7th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, AVR 2020, held in Lecce, Italy, in September 2020.* The 45 full papers and 14 short papers presented were carefully reviewed and selected from 99 submissions. The papers discuss key issues, approaches, ideas, open problems, innovative applications and trends in virtual reality, augmented reality, mixed reality, 3D reconstruction visualization, and applications in the areas of cultural heritage, medicine, education, and industry.
Augmented reality, virtual reality, and computer graphics ; 7th International conference, AVR 2020, Lecce, Italy, September 7–10, 2020, Proceedings, Part I
he 2-volume set LNCS 12242 and 12243 constitutes the refereed proceedings of the 7th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, AVR 2020, held in Lecce, Italy, in September 2020.* The 45 full papers and 14 short papers presented were carefully reviewed and selected from 99 submissions. The papers discuss key issues, approaches, ideas, open problems, innovative applications and trends in virtual reality, augmented reality, mixed reality, 3D reconstruction visualization, and applications in the areas of cultural heritage, medicine, education, and industry.
Augmented Humanity : Being and Remaining Agentic in a Digitalized World
This book will examine the implications of digitalization for the understanding of humanity, conceived as a community of intelligent agency. It addresses important topics across a range of social and behavioral theories and identifies a range of novel mechanisms and their social behavioral effects. Across the book, the author highlights the expansion of intelligent processing capability brought about by digitalization and the challenges this exposes for integrating artificial and human capabilities
Attention in Cognitive Systems : Theories and Systems from an Interdisciplinary Viewpoint ; 4th International Workshop on Attention in Cognitive Systems, WAPCV 2007 Hyderabad, India, January 8, 2007 Revised Selected Papers
The embodied nature of sensory-motor intelligence requires a continuous and focused interplay between the control of motor activities and the interpretation of feedback from perceptual modalities. Decision making about the selection of information from the incoming sensory stream – in tune with contextual processing on a current task and an agent’s global objectives – becomes a further challenging issue in attentional control. Attention must operate at interfaces between bottom-up driven world int- pretation and top-down driven information selection, thus acting at the core of arti?cial cognitive systems. These insights have already induced changes in AI-related disciplines, such as the design of behavior-based robot control and the computational modeling of animats. Today, the development of enabling technologiessuch as autonomous robotic systems,miniaturizedmobile–evenwearable–sensors,andambientintelligence systems involves the real-time analysis of enormous quantities of data. These data have to be processed in an intelligent way to provide “on time delivery” of the required relevant information. Knowledge has to be applied about what needs to be attended to, and when, and what to do in a meaningful sequence, in correspondence with visual feedback.
Assistive technologies, robotics, and automated machines in the health domain
The field of healthcare is constantly evolving and advancing with new technologies and innovations. Among these, assistive technologies, robotics, and automated machines are rapidly gaining ground as powerful tools to improve the quality of care and enhance patient outcomes. From wearable devices that monitor vital signs to surgical robots that assist in complex procedures, these technologies have the potential to revolutionize the way we deliver healthcare. The development and the integration of assistive technologies, care robots, and automated machines are strategic both as single components, when paired together, and when interconnected in the health domain.This reprint explores the latest developments in assistive technologies, robotics, and automated machines in the health domain, providing a comprehensive overview of their applications and potential impact. The reprint is for the benefit of healthcare professionals, researchers, engineers, and students interested in these rapidly evolving fields.
Artificiality and sustainability in entrepreneurship : Exploring the unforeseen, and paving the way to a sustainable future
Explores the past, present, and future of artificiality and sustainability in entrepreneurship – the unforeseen consequences and ways to advance to a sustainable future. In particular, it connects artificiality, sustainability and entrepreneurship, intertwining artificial with the specific phenomenon of those novel digital technologies that provoke continuous and significant change in our lives and business. Unlike digital entrepreneurship research, which focuses on digital technology development and management, this book covers processes and mechanisms of sustainable adaptability of entrepreneurs, the business logic of start-ups, and the collaborative behaviours under the mass digital transformation, including the prevalence of artificial intelligence. Some of the questions that this book answers are as follows: How has entrepreneurship reacted to such challenges previously? What lessons have been learned and need to be carried forward? How can entrepreneurship and the artefacts of entrepreneurship respond to current challenges? What should be the mindset of the entrepreneur to assure sustainable adaptation? How to embrace and embed the new business logic?
Artificial neural networks with Java : Tools for Building Neural Network Applications
Covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able to suggest various techniques of data preparation for many unconventional tasks. You will learn: Use Java for the development of neural network applications / Prepare data for many different tasks / Carry out some unusual neural network processing / Use a neural network to process non-continuous functions / Develop a program that recognizes handwritten digits
Artificial neural networks in Pattern Recognition ; 9th IAPR TC3 Workshop, ANNPR 2020, Winterthur, Switzerland, September 2–4, 2020, Proceedings
This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.
Artificial neural networks in Pattern Recognition ; 3d IAPR Workshop, ANNPR 2008 Paris, France, July 2-4, 2008 Proceedings
Constitutes the refereed proceedings of the Third TC3 IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2008, held in Paris, France, in July 2008.
Artificial neural networks : Recent advances, new perspectives and applications
This book explores the potential of ANNs for applications in different fields. Itincludes eight chapters that discuss deep learning, ANN tools, and other cutting-edgetechnologies. It also suggests avenues for further research into ANN techniques formedical imaging to detect breast tumors, classification of COVID-19 surveillancedatasets, health management, estimation of materials processing parameters, solarenergy management, and control of a petrochemical unit.
Artificial neural networks : Formal Models and Their Applications – ICANN 2005 ; 15th International Conference, Warsaw, Poland, September 11-15, 2005, Proceedings, Part II
The second volume contains 162 contributions related to Formal Models and their Applications and deals with new neural network models, supervised learning algorithms, ensemble-based learning, unsupervised learning, recurent neural networks, reinforcement learning, bayesian approaches to learning, learning theory, artificial neural networks for system modeling, decision making, optimalization and control, knowledge extraction from neural networks, temporal data analysis, prediction and forecasting, support vector machines and kernel-based methods, soft computing methods for data representation, analysis and processing, data fusion for industrial, medical and environmental applications, non-linear predictive models for speech processing, intelligent multimedia and semantics, applications to natural language processing, various applications, computational intelligence in games, and issues in hardware implementation.
