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cs.LG2024
Performance of NPG in Countable State-Space Average-Cost RL
Yashaswini Murthy, Isaac Grosof, Siva Theja Maguluri +1
We consider policy optimization methods in reinforcement learning settings where the state space is arbitrarily large, or even countably infinite. The motivation arises from contro…
cs.LG2024
Convergence of Natural Policy Gradient for a Family of Infinite-State Queueing MDPs
Isaac Grosof, Siva Theja Maguluri, R. Srikant
A wide variety of queueing systems can be naturally modeled as infinite-state Markov Decision Processes (MDPs). In the reinforcement learning (RL) context, a variety of algorithms…