Search Results for author: Zuyue Fu

Found 10 papers, 2 papers with code

Offline Reinforcement Learning for Human-Guided Human-Machine Interaction with Private Information

no code implementations23 Dec 2022 Zuyue Fu, Zhengling Qi, Zhuoran Yang, Zhaoran Wang, Lan Wang

To tackle the distributional mismatch, we leverage the idea of pessimism and use our OPE method to develop an off-policy learning algorithm for finding a desirable policy pair for both Alice and Bob.

Decision Making Off-policy evaluation +1

Offline Reinforcement Learning with Instrumental Variables in Confounded Markov Decision Processes

no code implementations18 Sep 2022 Zuyue Fu, Zhengling Qi, Zhaoran Wang, Zhuoran Yang, Yanxun Xu, Michael R. Kosorok

Due to the lack of online interaction with the environment, offline RL is facing the following two significant challenges: (i) the agent may be confounded by the unobserved state variables; (ii) the offline data collected a prior does not provide sufficient coverage for the environment.

Offline RL reinforcement-learning +1

False Correlation Reduction for Offline Reinforcement Learning

1 code implementation24 Oct 2021 Zhihong Deng, Zuyue Fu, Lingxiao Wang, Zhuoran Yang, Chenjia Bai, Tianyi Zhou, Zhaoran Wang, Jing Jiang

Offline reinforcement learning (RL) harnesses the power of massive datasets for resolving sequential decision problems.

D4RL Decision Making +3

Provably Efficient Generative Adversarial Imitation Learning for Online and Offline Setting with Linear Function Approximation

no code implementations19 Aug 2021 Zhihan Liu, Yufeng Zhang, Zuyue Fu, Zhuoran Yang, Zhaoran Wang

In generative adversarial imitation learning (GAIL), the agent aims to learn a policy from an expert demonstration so that its performance cannot be discriminated from the expert policy on a certain predefined reward set.

Imitation Learning

Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning

no code implementations19 Feb 2021 Luofeng Liao, Zuyue Fu, Zhuoran Yang, Yixin Wang, Mladen Kolar, Zhaoran Wang

Instrumental variables (IVs), in the context of RL, are the variables whose influence on the state variables are all mediated through the action.

Offline RL reinforcement-learning +2

Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy

no code implementations ICLR 2021 Zuyue Fu, Zhuoran Yang, Zhaoran Wang

To the best of our knowledge, we establish the rate of convergence and global optimality of single-timescale actor-critic with linear function approximation for the first time.

Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games

no code implementations ICLR 2020 Zuyue Fu, Zhuoran Yang, Yongxin Chen, Zhaoran Wang

We study discrete-time mean-field Markov games with infinite numbers of agents where each agent aims to minimize its ergodic cost.

Sample Elicitation

1 code implementation8 Oct 2019 Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang

We also show a connection between this sample elicitation problem and $f$-GAN, and how this connection can help reconstruct an estimator of the distribution based on collected samples.

Credible Sample Elicitation by Deep Learning, for Deep Learning

no code implementations25 Sep 2019 Yang Liu, Zuyue Fu, Zhuoran Yang, Zhaoran Wang

While classical elicitation results apply to eliciting a complex and generative (and continuous) distribution $p(x)$ for this image data, we are interested in eliciting samples $x_i \sim p(x)$ from agents.

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