30 citations · 75 across the 31 of their papers we have counts for
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cs.LG2021★ 2 cited
Common Information based Approximate State Representations in Multi-Agent Reinforcement Learning
Hsu Kao, Vijay Subramanian
Due to information asymmetry, finding optimal policies for Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) is hard with the complexity growing doubly expo…
cs.LG2020
Empirical Policy Evaluation with Supergraphs
Daniel Vial, Vijay Subramanian
We devise and analyze algorithms for the empirical policy evaluation problem in reinforcement learning. Our algorithms explore backward from high-cost states to find high-value one…