Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Carleman Estimates in Mean Field Games: Stability and Uniqueness for Nonlinear Pdes and Inverse Problems

Carleman Estimates in Mean Field Games: Stability and Uniqueness for Nonlinear Pdes and Inverse Problems

Klibanov, Michael V.
Li, Jingzhi

Hardcover

Series: Inverse and Ill-Posed Problems, Book 64

Business GeneralGeneral ComputersGeneral Mathematics

ISBN10: 3111722511
ISBN13: 9783111722511
Publisher: de Gruyter
Published: Jun 2 2025
Pages: 160
Weight: 1.01
Height: 0.44 Width: 6.69 Depth: 9.61
Language: English

This book provides a comprehensive exploration of Mean Field Games (MFG) theory, a mathematical framework for modeling the collective behavior of rational agents in complex systems. MFG theory can govern a range of societal phenomena, including finance, sociology, machine learning, and economics. The focus is on the system of two coupled nonlinear parabolic partial differential equations (PDEs) that define the Mean Field Games System. The book covers key theoretical topics such as solution stability and uniqueness, with a particular emphasis on Carleman estimates, which are used to estimate solution errors based on noise in the input data. It also introduces the theory of Ill-Posed and Inverse Problems within MFG theory. Both theoretical and numerical aspects of forward and inverse problems are explored through Carleman estimates, offering a rigorous foundation for researchers and practitioners in applied mathematics and related fields.

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