16 citations · 20 across the 6 of their papers we have counts for
5 papers · 1 filter
Linear Convergence of Independent Natural Policy Gradient in Games with Entropy Regularization
Youbang Sun, Tao Liu, P. R. Kumar +1
This work focuses on the entropy-regularized independent natural policy gradient (NPG) algorithm in multi-agent reinforcement learning. In this work, agents are assumed to have acc…
Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games
Youbang Sun, Tao Liu, Ruida Zhou +2
This work studies an independent natural policy gradient (NPG) algorithm for the multi-agent reinforcement learning problem in Markov potential games. It is shown that, under mild…
Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation
Ruida Zhou, Tao Liu, Min Cheng +3
We study robust reinforcement learning (RL) with the goal of determining a well-performing policy that is robust against model mismatch between the training simulator and the testi…
Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales
Tao Liu, P. R. Kumar, Ruida Zhou +1
Motivated by the problem of learning with small sample sizes, this paper shows how to incorporate into support-vector machines (SVMs) those properties that have made convolutional…
Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs
Tao Liu, Ruida Zhou, Dileep Kalathil +2
We address the issue of safety in reinforcement learning. We pose the problem in an episodic framework of a constrained Markov decision process. Existing results have shown that it…