Author

Maryam Kamgarpour

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#machine learning Preprint Oct 2026

Finite-Time Guarantees for Constrained Reinforcement Learning under Partial Observability

We study reinforcement learning in constrained partially observable Markov decision processes (CPOMDPs), where an agent maximizes reward subject to a cost constraint using only incomplete information about the underlying state. The lack of state observability may require optimal policies to depend on arbitrarily long o...

Valentina Zaccaria, P. Jordan, Ting-Ting Ni et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Provably Safe Sim-to-Real Transfer

The real-world sample complexity bound characterizes the benefit of using the simulator in terms of the sim-to-real mismatch, and formulates safe sim-to-real transfer within the framework of reward-free safe RL.

Tingting Ni, Maryam Kamgarpour · 0 citations