This research topic centers on the practical application of game theory and optimization methods to address complex challenges in real-world contexts. At its core, game theory provides a framework for analyzing strategic interactions among rational decision-makers, while optimization techniques are designed to seek the most favorable outcomes. These tools have proven to be powerful assets across a wide range of domains, from economics and computer science to social sciences and engineering. The following objectives guide this exploration: (i) Understanding Game Theory and Optimization in Real-world Contexts: This objective involves investigating how these mathematical constructs are applied to model and resolve problems across various fields. (ii) Analyzing the Effectiveness of Game Theory and Optimization Techniques: This involves studying real-world case studies and practical applications with the goal of evaluating the performance and efficiency of these methods in practice. (iii) Identifying Potential Areas for Effective Application of Game Theory and Optimization: This objective aims to pinpoint sectors or disciplines that may significantly benefit from the application of these mathematical techniques. The goal of this Research Topic in Frontiers in Physics aims to produce a comprehensive understanding of the real-world applications of game theory and optimization, highlighting their practical impact and potential for future use. It will provide valuable insights for professionals and researchers working in the fields where these techniques can be applied and contribute to the body of knowledge in game theory and optimization. Potential topics include but are not limited to the following: 1. Economics and Business: How are game theory and optimization used to make strategic business decisions and to understand economic phenomena? 2. Computer Science: How do these techniques contribute to areas like network design, machine learning, and algorithm development? 3. Social Sciences: How can game theory and optimization help in understanding social dynamics, designing policies, and resolving conflicts? 4. Engineering and Operations Research: How are these techniques utilized in system design, process optimization, and decision-making?

In this book applications of cooperative game theory that arise from combinatorial optimization problems are described. It is well known that the mathematical modeling of various real-world decision-making situations gives rise to combinatorial optimization problems. For situations where more than one decision-maker is involved classical combinatorial optimization theory does not suffice and it is here that cooperative game theory can make an important contribution. If a group of decision-makers decide to undertake a project together in order to increase the total revenue or decrease the total costs, they face two problems. The first one is how to execute the project in an optimal way so as to increase revenue. The second one is how to divide the revenue attained among the participants. It is with this second problem that cooperative game theory can help. The solution concepts from cooperative game theory can be applied to arrive at revenue allocation schemes. In this book the type of problems described above are examined. Although the choice of topics is application-driven, it also discusses theoretical questions that arise from the situations that are studied. For all the games described attention will be paid to the appropriateness of several game-theoretic solution concepts in the particular contexts that are considered. The computation complexity of the game-theoretic solution concepts in the situation at hand will also be considered.

Introduces various modeling and simulation methods and paradigms that are used to explain and solve the predominant challenges facing society Handbook of Real-World Applications in Modeling and Simulation provides a thorough explanation of modeling and simulation in the most useful, current, and predominant applied areas of transportation, homeland security, medicine, operational research, military science, and business modeling. Offering a cutting-edge and accessible presentation, this book discusses how and why the presented domains have become leading applications of modeling and simulation techniques. Contributions from leading academics and researchers integrate modeling and simulation theories, methods, and data to analyze challenges that involve technological and social issues. The book begins with an introduction that explains why modeling and simulation is a reliable analysis assessment tool for complex systems problems. Subsequent chapters provide an orientation to various modeling and simulation methods and paradigms that are used to explain and solve the predominant challenges across real-world applied domains. Additionally, the handbook: Provides a practical one-stop reference on modeling and simulation and contains an accessible introduction to key concepts and techniques Introduces, trains, and prepares readers from statistics, mathematics, engineering, computer science, economics, and business to use modeling and simulation in their studies and research Features case studies that are representative of fundamental areas of multidisciplinary studies and provides a concise look at the key concepts of modeling and simulation Contains a collection of original ideas on modeling and simulation to help academics and practitioners develop a multifunctional perspective Self-contained chapters offer a comprehensive approach to explaining each respective domain and include sections that explore the related history, theory, modeling paradigms, and case studies. Key terms and techniques are clearly outlined, and exercise sets allow readers to test their comprehension of the presented material. Handbook of Real-World Applications in Modeling and Simulation is an essential reference for academics and practitioners in the areas of operations research, business, management science, engineering, statistics, mathematics, and computer science. The handbook is also a suitable supplement for courses on modeling and simulation at the graduate level.

To make the best decisions, you need the best information. However, because most issues in game theory are grey, nearly all recent research has been carried out using a simplified method that considers grey systems as white ones. This often results in a forecasting function that is far from satisfactory when applied to many real situations. Grey Ga

Praise for the Second Edition: "This is quite a well-done book: very tightly organized, better-than-average exposition, and numerous examples, illustrations, and applications." —Mathematical Reviews of the American Mathematical Society An Introduction to Linear Programming and Game Theory, Third Edition presents a rigorous, yet accessible, introduction to the theoretical concepts and computational techniques of linear programming and game theory. Now with more extensive modeling exercises and detailed integer programming examples, this book uniquely illustrates how mathematics can be used in real-world applications in the social, life, and managerial sciences, providing readers with the opportunity to develop and apply their analytical abilities when solving realistic problems. This Third Edition addresses various new topics and improvements in the field of mathematical programming, and it also presents two software programs, LP Assistant and the Solver add-in for Microsoft Office Excel, for solving linear programming problems. LP Assistant, developed by coauthor Gerard Keough, allows readers to perform the basic steps of the algorithms provided in the book and is freely available via the book's related Web site. The use of the sensitivity analysis report and integer programming algorithm from the Solver add-in for Microsoft Office Excel is introduced so readers can solve the book's linear and integer programming problems. A detailed appendix contains instructions for the use of both applications. Additional features of the Third Edition include: A discussion of sensitivity analysis for the two-variable problem, along with new examples demonstrating integer programming, non-linear programming, and make vs. buy models Revised proofs and a discussion on the relevance and solution of the dual problem A section on developing an example in Data Envelopment Analysis An outline of the proof of John Nash's theorem on the existence of equilibrium strategy pairs for non-cooperative, non-zero-sum games Providing a complete mathematical development of all presented concepts and examples, Introduction to Linear Programming and Game Theory, Third Edition is an ideal text for linear programming and mathematical modeling courses at the upper-undergraduate and graduate levels. It also serves as a valuable reference for professionals who use game theory in business, economics, and management science.

An introduction to game theory that offers not only theoretical tools but also the intuition and behavioral insights to apply these tools to real-world situations. This introductory text on game theory provides students with both the theoretical tools to analyze situations through the logic of game theory and the intuition and behavioral insights to apply these tools to real-world situations. It is unique among game theory texts in offering a clear, formal introduction to standard game theory while incorporating evidence from experimental data and introducing recent behavioral models. Students will not only learn about incentives, how to represent situations as games, and what agents “should” do in these situations, but they will also be presented with evidence that either confirms the theoretical assumptions or suggests a way in which the theory might be updated. Features: Each chapter begins with a motivating example that can be run as an experiment and ends with a discussion of the behavior in the example. Parts I–IV cover the fundamental “nuts and bolts” of any introductory game theory course, including the theory of games, simple games with simultaneous decision making by players, sequential move games, and incomplete information in simultaneous and sequential move games. Parts V–VII apply the tools developed in previous sections to bargaining, cooperative game theory, market design, social dilemmas, and social choice and voting. Part VIII offers a more in-depth discussion of behavioral game theory models including evolutionary and psychological game theory. Supplemental material on the book’s website include solutions to end-of-chapter exercises, a manual for running each chapter’s experimental games using pencil and paper, and the oTree codes for running the games online.

This book on game theory introduces and develops the key concepts with a minimum of mathematics. Students are presented with empirical evidence, anecdotes and strategic situations to help them apply theory and gain a genuine insight into human behaviour. The book provides a diverse collection of examples and scenarios from history, literature, sports, crime, theology, war, biology, and everyday life. These examples come with rich context that adds real-world meat to the skeleton of theory. Each chapter begins with a specific strategic situation and is followed with a systematic treatment that gradually builds understanding of the concept.