Download or read book Choice Computing Machine Learning and Systemic Economics for Choosing written by Parag Kulkarni and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents thoughts and pathways to build revolutionary machine learning models with the new paradigm of machine learning to adapt behaviorism. It focuses on two aspects - one focuses on architecting a choice process to lead users on the certain choice path while the second focuses on developing machine learning models based on choice paradigm. This book is divided in three parts where part one deals with human choice and choice architecting models with stories of choice architects. Second part closely studies human choosing models and deliberates on developing machine learning models based on the human choice paradigm. Third part takes you further to look at machine learning based choice architecture. The proposed pioneering choice-based paradigm for machine learning presented in the book will help readers to develop products - help readers to solve problems in a more humanish way and to negotiate with uncertainty in a more graceful but in an objective way. It will help to create unprecedented value for business and society. Further, it will unveil a new paradigm for modern intelligent businesses to embark on the new journey; the journey of transition from shackled feature rich and choice poor systems to feature flexible and choice rich natural behaviors.

Download or read book Choice Computing Machine Learning and Systemic Economics for Choosing written by Parag Kulkarni and published by Springer Nature. This book was released on 2022-08-28 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents thoughts and pathways to build revolutionary machine learning models with the new paradigm of machine learning to adapt behaviorism. It focuses on two aspects – one focuses on architecting a choice process to lead users on the certain choice path while the second focuses on developing machine learning models based on choice paradigm. This book is divided in three parts where part one deals with human choice and choice architecting models with stories of choice architects. Second part closely studies human choosing models and deliberates on developing machine learning models based on the human choice paradigm. Third part takes you further to look at machine learning based choice architecture. The proposed pioneering choice-based paradigm for machine learning presented in the book will help readers to develop products – help readers to solve problems in a more humanish way and to negotiate with uncertainty in a more graceful but in an objective way. It will help to create unprecedented value for business and society. Further, it will unveil a new paradigm for modern intelligent businesses to embark on the new journey; the journey of transition from shackled feature rich and choice poor systems to feature flexible and choice rich natural behaviors.

Download or read book Explainable Interpretable and Transparent AI Systems written by B. K. Tripathy and published by CRC Press. This book was released on 2024-08-23 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transparent Artificial Intelligence (AI) systems facilitate understanding of the decision-making process and provide opportunities in various aspects of explaining AI models. This book provides up-to-date information on the latest advancements in the field of explainable AI, which is a critical requirement of AI, Machine Learning (ML), and Deep Learning (DL) models. It provides examples, case studies, latest techniques, and applications from domains such as healthcare, finance, and network security. It also covers open-source interpretable tool kits so that practitioners can use them in their domains. Features: Presents a clear focus on the application of explainable AI systems while tackling important issues of “interpretability” and “transparency”. Reviews adept handling with respect to existing software and evaluation issues of interpretability. Provides insights into simple interpretable models such as decision trees, decision rules, and linear regression. Focuses on interpreting black box models like feature importance and accumulated local effects. Discusses capabilities of explainability and interpretability. This book is aimed at graduate students and professionals in computer engineering and networking communications.

Download or read book AI Consciousness and The New Humanism written by Sangeetha Menon and published by Springer Nature. This book was released on with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Ethics in Online AI Based Systems written by Santi Caballé and published by Elsevier. This book was released on 2024-04-19 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent technological advancements have deeply transformed society and the way people interact with each other. Instantaneous communication platforms have allowed connections with other people, forming global communities, and creating unprecedented opportunities in many sectors, making access to online resources more ubiquitous by reducing limitations imposed by geographical distance and temporal constrains. These technological developments bear ethically relevant consequences with their deployment, and legislations often lag behind such advancements. Because the appearance and deployment of these technologies happen much faster than legislative procedures, the way these technologies affect social interactions have profound ethical effects before any legislative regulation can be built, in order to prevent and mitigate those effects. Ethics in Online AI-Based Systems: Risks and Opportunities in Current Technological Trends features a series of reflections from experts in different fields on potential ethically relevant outcomes that upcoming technological advances could bring about in our society. Creating a space to explore the ethical relevance that technologies currently still under development could have constitutes an opportunity to better understand how these technologies could or should not be used in the future in order to maximize their ethically beneficial outcomes, while avoiding potential detrimental effects. Stimulating reflection and considerations with respect to the design, deployment and use of technology will help guide current and future technological advancements from an ethically informed position in order to ensure that, tomorrow, such advancements could contribute towards solving current global and social challenges that we, as a society, have today. This will not only be useful for researchers and professional engineers, but also for educators, policy makers, and ethicists. Investigates how "intelligent" technological advances might be used, how they will affect social interactions, and what ethical consequences they might have for society Identifies and reflects on questions that need to be asked before the design, deployment, and application of upcoming technological advancements, aiming to both prevent and mitigate potential risks, as well as to identify potentially ethically-beneficial opportunities Recognizes the huge potential for ethically-relevant outcomes that technological advancements have, and take proactive steps to anticipate that they be designed from an ethically-informed position Provides reflections that highlight the importance of the relationship between technology, their users and our society, thus encouraging informed design and educational and legislative approaches that take this relationship into account

Download or read book A Short Introduction to Preferences written by Francesca Bellet and published by Springer Nature. This book was released on 2022-06-01 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational social choice is an expanding field that merges classical topics like economics and voting theory with more modern topics like artificial intelligence, multiagent systems, and computational complexity. This book provides a concise introduction to the main research lines in this field, covering aspects such as preference modelling, uncertainty reasoning, social choice, stable matching, and computational aspects of preference aggregation and manipulation. The book is centered around the notion of preference reasoning, both in the single-agent and the multi-agent setting. It presents the main approaches to modeling and reasoning with preferences, with particular attention to two popular and powerful formalisms, soft constraints and CP-nets. The authors consider preference elicitation and various forms of uncertainty in soft constraints. They review the most relevant results in voting, with special attention to computational social choice. Finally, the book considers preferences in matching problems. The book is intended for students and researchers who may be interested in an introduction to preference reasoning and multi-agent preference aggregation, and who want to know the basic notions and results in computational social choice. Table of Contents: Introduction / Preference Modeling and Reasoning / Uncertainty in Preference Reasoning / Aggregating Preferences / Stable Marriage Problems

Download or read book The Economics of Artificial Intelligence written by Ajay Agrawal and published by University of Chicago Press. This book was released on 2024-03-05 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book A Short Introduction to Preferences written by Francesca Rossi and published by Morgan & Claypool Publishers. This book was released on 2011-09-09 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational social choice is an expanding field that merges classical topics like economics and voting theory with more modern topics like artificial intelligence, multiagent systems, and computational complexity. This book provides a concise introduction to the main research lines in this field, covering aspects such as preference modelling, uncertainty reasoning, social choice, stable matching, and computational aspects of preference aggregation and manipulation. The book is centered around the notion of preference reasoning, both in the single-agent and the multi-agent setting. It presents the main approaches to modeling and reasoning with preferences, with particular attention to two popular and powerful formalisms, soft constraints and CP-nets. The authors consider preference elicitation and various forms of uncertainty in soft constraints. They review the most relevant results in voting, with special attention to computational social choice. Finally, the book considers preferences in matching problems. The book is intended for students and researchers who may be interested in an introduction to preference reasoning and multi-agent preference aggregation, and who want to know the basic notions and results in computational social choice. Table of Contents: Introduction / Preference Modeling and Reasoning / Uncertainty in Preference Reasoning / Aggregating Preferences / Stable Marriage Problems

Download or read book Machine Intelligence for Smart Applications written by Amina Adadi and published by Springer Nature. This book was released on 2023-08-24 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides insights into recent advances in Machine Intelligence (MI) and related technologies, identifies risks and challenges that are, or could be, slowing down overall MI mainstream adoption and innovation efforts, and discusses potential solutions to address these limitations. All these aspects are explored through the lens of smart applications. The book navigates the landscape of the most recent, prominent, and impactful MI smart applications. The broad set of smart applications for MI is organized into four themes covering all areas of the economy and social life, namely (i) Smart Environment, (ii) Smart Social Living, (iii) Smart Business and Manufacturing, and (iv) Smart Government. The book examines not only present smart applications but also takes a look at how MI may potentially be applied in the future. This book is aimed at researchers and postgraduate students in applied artificial intelligence and allied technologies. The book is also valuable for practitioners, and it serves as a bridge between researchers and practitioners. It also helps connect researchers interested in MI technologies who come from different social and business disciplines and who can benefit from sharing ideas and results.

Download or read book Advanced Computing and Systems for Security written by Rituparna Chaki and published by Springer. This book was released on 2015-11-05 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book contains the extended version of the works that have been presented and discussed in the Second International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2015) held during May 23-25, 2015 in Kolkata, India. The symposium has been jointly organized by the AGH University of Science & Technology, Cracow, Poland; Ca’ Foscari University, Venice, Italy and University of Calcutta, India. The book is divided into volumes and presents dissertation works in the areas of Image Processing, Biometrics-based Authentication, Soft Computing, Data Mining, Next Generation Networking and Network Security, Remote Healthcare, Communications, Embedded Systems, Software Engineering and Service Engineering.

Download or read book Artificial Intelligence and Economic Theory Skynet in the Market written by Tshilidzi Marwala and published by Springer. This book was released on 2017-09-18 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book theoretically and practically updates major economic ideas such as demand and supply, rational choice and expectations, bounded rationality, behavioral economics, information asymmetry, pricing, efficient market hypothesis, game theory, mechanism design, portfolio theory, causality and financial engineering in the age of significant advances in man-machine systems. The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence concepts such as the swarming of birds, the working of the brain and the pathfinding of the ants. Artificial Intelligence and Economic Theory: Skynet in the Market analyses the impact of artificial intelligence on economic theories, a subject that has not been studied. It also introduces new economic theories and these are rational counterfactuals and rational opportunity costs. These ideas are applied to diverse areas such as modelling of the stock market, credit scoring, HIV and interstate conflict. Artificial intelligence ideas used in this book include neural networks, particle swarm optimization, simulated annealing, fuzzy logic and genetic algorithms. It, furthermore, explores ideas in causality including Granger as well as the Pearl causality models.

Download or read book Empirical Asset Pricing written by Wayne Ferson and published by MIT Press. This book was released on 2019-03-12 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.

Download or read book Introduction to Machine Learning Professional Level written by CPA John Kimani and published by Finstock Evarsity Publishers. This book was released on 2023-08-01 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: BOOK SUMMARY The main topics in this book are; • Introduction to Machine Learning • Data Preprocessing and Cleaning • Supervised Learning • Supervised Learning • Unsupervised Learning • Unsupervised Learning • Model Evaluation and Selection • Model Deployment and Applications “Introduction to Machine Learning” is a comprehensive and well-structured book that delves into the core principles and methodologies of machine learning. The book emphasizes a hands-on approach, providing readers with the necessary tools and techniques to build and deploy machine learning models effectively.

Download or read book Powering the Digital Economy Opportunities and Risks of Artificial Intelligence in Finance written by El Bachir Boukherouaa and published by International Monetary Fund. This book was released on 2021-10-22 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

Download or read book Computational Intelligence in Economics and Finance written by Paul P. Wang and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the ability to handle specific characteristics of economics and finance forecasting problems like e.g. non-linear relationships, behavioral changes, or knowledge-based domain segmentation, we have recently witnessed a phenomenal growth of the application of computational intelligence methodologies in this field. In this volume, Chen and Wang collected not just works on traditional computational intelligence approaches like fuzzy logic, neural networks, and genetic algorithms, but also examples for more recent technologies like e.g. rough sets, support vector machines, wavelets, or ant algorithms. After an introductory chapter with a structural description of all the methodologies, the subsequent parts describe novel applications of these to typical economics and finance problems like business forecasting, currency crisis discrimination, foreign exchange markets, or stock markets behavior.

Download or read book 26th European Symposium on Computer Aided Process Engineering written by and published by Elsevier. This book was released on 2016-06-17 with total page 2486 pages. Available in PDF, EPUB and Kindle. Book excerpt: 26th European Symposium on Computer Aided Process Engineering contains the papers presented at the 26th European Society of Computer-Aided Process Engineering (ESCAPE) Event held at Portorož Slovenia, from June 12th to June 15th, 2016. Themes discussed at the conference include Process-product Synthesis, Design and Integration, Modelling, Numerical analysis, Simulation and Optimization, Process Operations and Control and Education in CAPE/PSE. Presents findings and discussions from the 26th European Society of Computer-Aided Process Engineering (ESCAPE) Event

Download or read book Data Science for Economics and Finance written by Sergio Consoli and published by Springer Nature. This book was released on 2021 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.