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This book includes chapters by experts from developing and developed countries that apply game theory to issues in natural resources and the environment, demonstrating the usefulness of game theory in policy-making and appealing to a wide audience.
In this book, different quantitative approaches to the study of electoral systems have been developed: game-theoretic, decision-theoretic, statistical, probabilistic, combinatorial, geometric, and optimization ones. All the authors are prominent scholars from these disciplines. Quantitative approaches offer a powerful tool to detect inconsistencies or poor performance in actual systems. Applications to concrete settings such as EU, American Congress, regional, and committee voting are discussed.
Applied Mathematics with Open-source Software: Operational Research Problems with Python and R is aimed at a broad segment of readers who wish to learn how to use open-source software to solve problems in applied mathematics. The book has an innovative structure with 4 sections of two chapters covering a large range of applied mathematical techniques: probabilistic modelling, dynamical systems, emergent behaviour and optimisation. The pairs of chapters in each section demonstrate different families of solution approaches. Each chapter starts with a problem, gives an overview of the relevant theory, shows a solution approach in R and in Python, and finally gives wider context by including a n...
Essays on Cooperative Games collates selected contributions on Cooperative Games. The papers cover both theoretical aspects (Coalition Formation, Values, Simple Games and Dynamic Games) and applied aspects (in Finance, Production, Transportation and Market Games). A contribution on Minimax Theorem (by Ken Binmore) and a brief history of early Game Theory (by Gianfranco Gambarelli and Guillermo Owen) are also enclosed.
These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as performance optimization in IoT, big data, reliability, privacy, security, service selection, QoS and machine learning. This thirty-fourth issue contains 12 selected papers which present new findings and innovative methodologies as well as discuss issues and challenges in the field of collective intelligence in group decision making with special emphasize given to voting theory, power indices and graphs while addressing elections, social choices, IoT and allocation algorithms.
The most difficult part of making decisions in the health care field on all levels (national, regional, institutional, patient) is linked to the very complexity of the system itself, to the intrinsic uncertainty involved and its dynamic nature. This requires not only the ability to analyze and interpret a large amount of information but also arrange it so that it becomes a cognitive base for appropriate decision-making. Moreover, decisions in the health care field are subjected to many challenges and constraints: fast change and uncertain outcomes, aging population, increasing citizen expectations, equity considerations and limited resources. Operations research, statistical and economic-rel...