Random Features for High-Dimensional Nonlocal Mean-Field Games
Sudhanshu Agrawal,
Wonjun Lee,
Samy Wu Fung
et al.
Abstract:We propose an efficient solution approach for high-dimensional nonlocal meanfield game (MFG) systems based on the Monte Carlo approximation of interaction kernels via random features. We avoid costly space-discretizations of interaction terms in the state-space by passing to the feature-space. This approach allows for a seamless mean-field extension of virtually any single-agent trajectory optimization algorithm. Here, we extend the direct transcription approach in optimal control to the mean-field setting. We… Show more
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