16 citations · 20 across the 6 of their papers we have counts for
6 papers
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…
A Biologically Plausible Learning Rule for Perceptual Systems of organisms that Maximize Mutual Information
Tao Liu
It is widely believed that the perceptual system of an organism is optimized for the properties of the environment to which it is exposed. A specific instance of this principle kno…
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…