3 citations · 9 across the 10 of their papers we have counts for
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cs.LG2022★ 1 cited
Policy Gradient for Reinforcement Learning with General Utilities
Navdeep Kumar, Kaixin Wang, Kfir Levy +1
In Reinforcement Learning (RL), the goal of agents is to discover an optimal policy that maximizes the expected cumulative rewards. This objective may also be viewed as finding a p…
cs.AI2022★ 2 cited
Efficient Policy Iteration for Robust Markov Decision Processes via Regularization
Navdeep Kumar, Kfir Levy, Kaixin Wang +1
Robust Markov decision processes (MDPs) provide a general framework to model decision problems where the system dynamics are changing or only partially known. Efficient methods for…
cs.LG2022★ 1 cited
The Geometry of Robust Value Functions
Kaixin Wang, Navdeep Kumar, Kuangqi Zhou +3
The space of value functions is a fundamental concept in reinforcement learning. Characterizing its geometric properties may provide insights for optimization and representation. E…