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math.OC2022★ 3 cited
Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
Batuhan Yardim, Semih Cayci, Matthieu Geist +1
Mean-field games have been used as a theoretical tool to obtain an approximate Nash equilibrium for symmetric and anonymous -player games. However, limiting applicability, exist…
cs.LG2022★ 1 cited
Finite-Time Analysis of Entropy-Regularized Neural Natural Actor-Critic Algorithm
Semih Cayci, Niao He, R. Srikant
Natural actor-critic (NAC) and its variants, equipped with the representation power of neural networks, have demonstrated impressive empirical success in solving Markov decision pr…
cs.LG2022
Finite-Time Analysis of Natural Actor-Critic for POMDPs
Semih Cayci, Niao He, R. Srikant
We consider the reinforcement learning problem for partially observed Markov decision processes (POMDPs) with large or even countably infinite state spaces, where the controller ha…