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Regularity Theory for Mean-Field Game Systems
Beginning with a concise introduction to the theory of mean-field games (MFGs), this book presents the key elements of the regularity theory for MFGs. It then introduces a series of techniques for well-posedness in the context of mean-field problems, including stationary and time-dependent MFGs, subquadratic and superquadratic MFG formulations, and distinct classes of mean-field couplings. It also explores stationary and time-dependent MFGs through a series of a-priori estimates for solutions of the Hamilton-Jacobi and Fokker-Planck equation. It shows sophisticated a-priori systems derived using a range of analytical techniques, and builds on previous results to explain classical solutions. The final chapter discusses the potential applications, models and natural extensions of MFGs. As MFGs connect common problems in pure mathematics, engineering, economics and data management, this book is a valuable resource for researchers and graduate students in these fields.
The Yezidi Oral Tradition in Iraqi Kurdistan
The Yezidis are a Kurdish-speaking religious minority, neither Muslim, Christian nor Jewish. Their ethnicity has been disputed, but most now claim Kurdish identity. Their heartland, including their holiest shrine, is in the Badinan province of Northern Iraq, and it is the communities in this area which are the main focus of this book. Their highly
Daily Report
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Machine Learning and Data Sciences for Financial Markets
Leveraging the research efforts of more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence. The text is structured around three main areas: 'Interactions with investors and asset owners,' which covers robo-advisors and price formation; 'Risk intermediation,' which discusses derivative hedging, portfolio construction, and machine learning for dynamic optimization; and 'Connections with the real economy,' which explores nowcasting, alternative data, and ethics of algorithms. Accessible to a wide audience, this invaluable resource will allow practitioners to include machine learning driven techniques in their day-to-day quantitative practices, while students will build intuition and come to appreciate the technical tools and motivation for the theory.
Pursuing the Just Cause of Their People
The Armenian terrorist movement is the subject of Michael Gunter's analysis. Beginning with an introductory overview of recent Armenian terrorist attacks against Turkish diplomats and property and perceived allies of the Turks, he then examines historical motivations and goals of the Armenian terrorist movement. Although the present wave of Armenian terrorism began only in the 1970s, Gunter traces its origins to the late nineteenth and early twentieth centuries. He outlines the so-called Armenian question which resulted in deportations and massacres of the Armenians by Turks during World War I, and questions where responsibility for the actions and reactions of the period lie. Gunter then fo...
Armenian Olympians
The book provides a coverage of all the Armenian olympians results and records from 1906 to 2004.
Inside Central Asia
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Mean Field Games
This volume is based on lectures delivered at the 2020 AMS Short Course “Mean Field Games: Agent Based Models to Nash Equilibria,” held January 13–14, 2020, in Denver, Colorado. Mean field game theory offers a robust methodology for studying large systems of interacting rational agents. It has been extraordinarily successful and has continued to develop since its inception. The six chapters that make up this volume provide an overview of the subject, from the foundations of the theory to applications in economics and finance, including computational aspects. The reader will find a pedagogical introduction to the main ingredients, from the forward-backward mean field game system to the master equation. Also included are two detailed chapters on the connection between finite games and mean field games, with a pedestrian description of the different methods available to solve the convergence problem. The volume concludes with two contributions on applications of mean field games and on existing numerical methods, with an opening to machine learning techniques.
