Download or read book Contributions to the Theory of Games AM 28 Volume II written by Harold William Kuhn and published by Princeton University Press. This book was released on 2016-03-02 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: These two new collections, numbers 28 and 29 respectively in the Annals of Mathematics Studies, continue the high standard set by the earlier Annals Studies 20 and 24 by bringing together important contributions to the theories of games and of nonlinear differential equations.
Download or read book Contributions to the Theory of Games written by Harold William Kuhn and published by Princeton University Press. This book was released on 1953-03-21 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: These two new collections, numbers 28 and 29 respectively in the Annals of Mathematics Studies, continue the high standard set by the earlier Annals Studies 20 and 24 by bringing together important contributions to the theories of games and of nonlinear differential equations.
Download or read book Theory and Applications of Dynamic Games written by Elena Parilina and published by Springer Nature. This book was released on 2022-11-23 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive overview of noncooperative and cooperative dynamic games involving uncertain parameter values, with the stochastic process being described by an event tree. Primarily intended for graduate students of economics, management science and engineering, the book is self-contained, as it defines and illustrates all relevant concepts originally introduced in static games before extending them to a dynamic framework. It subsequently addresses the sustainability of cooperative contracts over time and introduces a range of mechanisms to help avoid such agreements breaking down before reaching maturity. To illustrate the concepts discussed, the book provides various examples of how dynamic games played over event trees can be applied to environmental economics, management science, and engineering.
Download or read book Algorithmic Game Theory written by Xiaotie Deng and published by Springer. This book was released on 2018-08-26 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th International Symposium on Algorithmic Game Theory, SAGT 2018, held in Beijing, China, in September 2018. The 19 full papers presented together with 6 short papers and 5 plenary talks were carefully reviewed and selected from 54 submissions. The papers cover various important aspects of algorithmic game theory including market equilibrium, auctions and applications, two sided markets, cake-cutting, cooperative games, voting games, multi-agent scheduling, price of stability, various mechanism design problems: online-dynamics and multi-stages as well as revenue maximization and resource allocation and applications.
Download or read book Explainable Artificial Intelligence written by Luca Longo and published by Springer Nature. This book was released on with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of Third International Conference on Computing and Communication Networks written by Giancarlo Fortino and published by Springer Nature. This book was released on with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Principles and Applications of Adaptive Artificial Intelligence written by Lv, Zhihan and published by IGI Global. This book was released on 2024-01-24 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence, edited by Zhihan Lv from Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation problem in AI systems. It explores the latest concepts, technologies, and applications of Adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, real-world case studies, and thorough analysis, the Handbook provides practitioners with practical ideas and solutions, while also serving as a valuable teaching material and reference guide for students and educators in AI-related disciplines. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems, making it an indispensable resource for researchers, professionals, and students seeking to revolutionize their research and applications in the field of Adaptive AI.
Download or read book Practical Machine Learning with R written by Carsten Lange and published by CRC Press. This book was released on 2024-05-20 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is a comprehensive guide to machine learning and artificial intelligence tailored for students in business and economics. It takes a hands-on approach to teach machine learning, emphasizing practical applications over complex mathematical concepts. Students are not required to have advanced mathematics knowledge such as matrix algebra or calculus. The author introduces machine learning algorithms, utilizing the widely used R language for statistical analysis. Each chapter includes examples, case studies, and interactive tutorials to enhance understanding. No prior programming knowledge is needed. The book leverages the tidymodels package, an extension of R, to streamline data processing and model workflows. This package simplifies commands, making the logic of algorithms more accessible by minimizing programming syntax hurdles. The use of tidymodels ensures a unified experience across various machine learning models. With interactive tutorials that students can download and follow along at their own pace, the book provides a practical approach to apply machine learning algorithms to real-world scenarios. In addition to the interactive tutorials, each chapter includes a Digital Resources section, offering links to articles, videos, data, and sample R code scripts. A companion website further enriches the learning and teaching experience: https://ai.lange-analytics.com. This book is not just a textbook; it is a dynamic learning experience that empowers students and instructors alike with a practical and accessible approach to machine learning in business and economics. Key Features: Unlocks machine learning basics without advanced mathematics — no calculus or matrix algebra required. Demonstrates each concept with R code and real-world data for a deep understanding — no prior programming knowledge is needed. Bridges the gap between theory and real-world applications with hands-on interactive projects and tutorials in every chapter, guided with hints and solutions. Encourages continuous learning with chapter-specific online resources—video tutorials, R-scripts, blog posts, and an online community. Supports instructors through a companion website that includes customizable materials such as slides and syllabi to fit their specific course needs.
Download or read book Energy Systems Evaluation Volume 1 written by Jingzheng Ren and published by Springer Nature. This book was released on 2021-06-01 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents various methods for sustainability assessment of energy systems, under various different conditions and scenarios. It answers the questions of how to measure the sustainability of energy systems by adopting appropriate metrics and methods. This book provides readers with a comprehensive view of the frontiers of sustainability assessment methods for energy system analysis. It presents various methodologies, allowing readers to understand: the complete metrics for sustainability assessment; life cycle thinking for sustainability assessment of energy systems; and the advanced sustainability assessment methods for energy systems. This book is of interest to researchers, engineers, decision makers, and postgraduate students within the field of energy systems, sustainability, and decision analysis.
Download or read book XxAI Beyond Explainable AI written by Andreas Holzinger and published by Springer Nature. This book was released on 2022 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans. Explainable AI is receiving huge interest in the machine learning and AI research communities, across academia, industry, and government, and there is now an excellent opportunity to push towards successful explainable AI applications. This volume will help the research community to accelerate this process, to promote a more systematic use of explainable AI to improve models in diverse applications, and ultimately to better understand how current explainable AI methods need to be improved and what kind of theory of explainable AI is needed. After overviews of current methods and challenges, the editors include chapters that describe new developments in explainable AI. The contributions are from leading researchers in the field, drawn from both academia and industry, and many of the chapters take a clear interdisciplinary approach to problem-solving. The concepts discussed include explainability, causability, and AI interfaces with humans, and the applications include image processing, natural language, law, fairness, and climate science.
Download or read book Artificial Intelligence Learning and Computation in Economics and Finance written by Ragupathy Venkatachalam and published by Springer Nature. This book was released on 2023-02-15 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought. Through 16 chapters written by pioneers in economics, finance, computer science, psychology, complexity and statistics/econometrics, the book introduces their original research and presents the findings they have yielded. Theoretical and empirical studies featured in this book draw on a variety of approaches such as agent-based modeling, numerical simulations, computable economics, as well as employing tools from artificial intelligence and machine learning algorithms. The use of computational approaches to perform counterfactual thought experiments are also introduced, which help transcend the limits posed by traditional mathematical and statistical tools. The book also includes discussions on methodology, epistemology, history and issues concerning prediction, validation, and inference, all of which have become pertinent with the increasing use of computational approaches in economic analysis.
Download or read book Handbook of Game Theory and Industrial Organization Volume I written by Luis C. Corchón and published by Edward Elgar Publishing. This book was released on 2018-02-23 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first volume of this wide-ranging Handbook contains original contributions by world-class specialists. It provides up-to-date surveys of the main game-theoretic tools commonly used to model industrial organization topics. The Handbook covers numerous subjects in detail including, among others, the tools of lattice programming, supermodular and aggregative games, monopolistic competition, horizontal and vertically differentiated good models, dynamic and Stackelberg games, entry games, evolutionary games with adaptive players, asymmetric information, moral hazard, learning and information sharing models.
Download or read book Motion Planning for Autonomous Vehicles in Partially Observable Environments written by Taş, Ömer Şahin and published by KIT Scientific Publishing. This book was released on 2023-10-23 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in real-time, in two distinct ways: first, with nonlinear optimization, and secondly, by framing it as a partially observable Markov decision process and approximating the solution with sampling.
Download or read book Combinatorial Mathematics Optimal Designs and Their Applications written by and published by Elsevier. This book was released on 2011-08-26 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combinatorial Mathematics, Optimal Designs, and Their Applications
Download or read book Data Science and Machine Learning Applications in Subsurface Engineering written by Daniel Asante Otchere and published by CRC Press. This book was released on 2024-02-06 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers unsupervised learning, supervised learning, clustering approaches, feature engineering, explainable AI and multioutput regression models for subsurface engineering problems. Processing voluminous and complex data sets are the primary focus of the field of machine learning (ML). ML aims to develop data-driven methods and computational algorithms that can learn to identify complex and non-linear patterns to understand and predict the relationships between variables by analysing extensive data. Although ML models provide the final output for predictions, several steps need to be performed to achieve accurate predictions. These steps, data pre-processing, feature selection, feature engineering and outlier removal, are all contained in this book. New models are also developed using existing ML architecture and learning theories to improve the performance of traditional ML models and handle small and big data without manual adjustments. This research-oriented book will help subsurface engineers, geophysicists, and geoscientists become familiar with data science and ML advances relevant to subsurface engineering. Additionally, it demonstrates the use of data-driven approaches for salt identification, seismic interpretation, estimating enhanced oil recovery factor, predicting pore fluid types, petrophysical property prediction, estimating pressure drop in pipelines, bubble point pressure prediction, enhancing drilling mud loss, smart well completion and synthetic well log predictions.
Download or read book Explainable AI Interpreting Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Download or read book Federated Learning written by Lam M. Nguyen and published by Elsevier. This book was released on 2024-02-09 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Federated Learning: Theory and Practi ce provides a holisti c treatment to federated learning as a distributed learning system with various forms of decentralized data and features. Part I of the book begins with a broad overview of opti mizati on fundamentals and modeling challenges, covering various aspects of communicati on effi ciency, theoretical convergence, and security. Part II featuresemerging challenges stemming from many socially driven concerns of federated learning as a future public machine learning service. Part III concludes the book with a wide array of industrial applicati ons of federated learning, as well as ethical considerations, showcasing its immense potential for driving innovation while safeguarding sensitive data.Federated Learning: Theory and Practi ce provides a comprehensive and accessible introducti on to federated learning which is suitable for researchers and students in academia, and industrial practitioners who seek to leverage the latest advance in machine learning for their entrepreneurial endeavors. - Presents the fundamentals and a survey of key developments in the field of federated learning - Provides emerging, state-of-the art topics that build on fundamentals - Contains industry applications - Gives an overview of visions of the future
