Inverse problems for mean field games

Abstract

The theory of mean field games studies the limiting behaviors of large systems where the agents interact with each other in a certain symmetric way. The running and terminal costs are critical for the agents to decide the strategies. However, in practice they are often partially known or totally unknown for the agents, while the total cost is known at the end of the game. To address this challenging issue, we propose and study several inverse problems for mean field games. When the Lagrangian is a kinetic energy, we first establish unique identifiability results, showing that one can recover either the running cost or the terminal cost from knowledge of the total cost. If the running cost is limited to the time-independent class, we can further prove that one can simultaneously recover both the running and the terminal costs. Finally, we extend the results to the setup with general Lagrangians.

26 pages and comments are welcome

References in corpus (7)

• Inverse problems for mean field games
• Simultaneously recovering running cost and Hamiltonian in Mean Field Games system
• On an inverse boundary problem for mean field games
• The Mean Field Games System: Carleman Estimates, Lipschitz Stability and Uniqueness
• An Inverse Problem With the Final Overdetermination for the Mean Field Games System
• A mean field game inverse problem
• On The Mean Field Games System With the Lateral Cauchy Data via Carleman Estimates

Cited by in corpus (6)

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• On inverse problems in predator-prey models
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• Determining a parabolic system by boundary observation of its non-negative solutions with biological applications
• Determining state space anomalies in mean field games
• Decoding a mean field game by the Cauchy data around its unknown stationary states