Author

Tesshu Fujinami

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Preprint Sep 2026

Policy Gradient over History-Dependent Policy Classes for LQR with Domain Randomization

This work first study PG of domain randomized LQR over history-dependent policy classes, such as finite impulse response controllers, as they can extend the possibilities of simultaneous stabilization, and proposes a curriculum learning based algorithm which gradually expands the memory of the controller.

Tesshu Fujinami, Bruce D. Lee, Anastasios Tsiamis et al. · 0 citations